docs: update docs

* fix(datasets): expose a generator on EpisodeAwareSampler for distributed shuffle sync

In distributed training, accelerate can only synchronize the shuffle
permutation across ranks when the sampler exposes a generator attribute.
EpisodeAwareSampler shuffled via the global torch RNG, so disjoint batch
shards relied on every rank's global CPU RNG staying in lockstep forever;
any rank-asymmetric RNG consumption (e.g. eval rollouts on the main
process only) silently desynced the permutations and ranks trained on
overlapping/missing samples.

* fix(train): seed sampler generator and gate dataset download per node

- Pass a generator seeded with cfg.seed to EpisodeAwareSampler so
  accelerator.prepare registers it as the synchronized RNG and the
  shuffle order is reproducible.
- Gate the initial make_dataset call on is_local_main_process instead of
  is_main_process: the global main process only exists on node 0, so on
  every other node all local ranks were downloading the dataset and
  building the Arrow cache concurrently.

docs/source/hil_data_collection.mdx

@@ -57,11 +57,11 @@ The `lerobot-rollout --strategy.type=dagger` mode requires **teleoperators with
 
 **Compatible teleoperators:**
 
-- `openarm_mini` - OpenArm Mini
+- `bi_openarm_mini` - Bimanual OpenArm Mini
 - `so_leader` - SO100 / SO101 leader arm
 
 > [!IMPORTANT]
-> The provided commands default to `bi_openarm_follower` + `openarm_mini`.
+> The provided commands default to `bi_openarm_follower` + `bi_openarm_mini`.
 > `so_follower` + `so_leader` configs are also registered and can be used via CLI flags.
 
 ---
@@ -104,9 +104,9 @@ lerobot-rollout --strategy.type=dagger \
     --robot.right_arm_config.port=can0 \
     --robot.right_arm_config.side=right \
     --robot.cameras='{left_wrist: {type: opencv, index_or_path: "/dev/video0", width: 1280, height: 720, fps: 30}, right_wrist: {type: opencv, index_or_path: "/dev/video4", width: 1280, height: 720, fps: 30}, base: {type: opencv, index_or_path: "/dev/video2", width: 640, height: 480, fps: 30}}' \
-    --teleop.type=openarm_mini \
-    --teleop.port_left=/dev/ttyACM0 \
-    --teleop.port_right=/dev/ttyACM1 \
+    --teleop.type=bi_openarm_mini \
+    --teleop.left_arm_config.port=/dev/ttyACM0 \
+    --teleop.right_arm_config.port=/dev/ttyACM1 \
     --policy.path=outputs/pretrain/checkpoints/last/pretrained_model \
     --dataset.repo_id=your-username/rollout_hil_dataset \
     --dataset.single_task="Fold the T-shirt properly" \
@@ -131,9 +131,9 @@ lerobot-rollout --strategy.type=dagger \
     --robot.right_arm_config.port=can0 \
     --robot.right_arm_config.side=right \
     --robot.cameras='{left_wrist: {type: opencv, index_or_path: "/dev/video0", width: 1280, height: 720, fps: 30}, right_wrist: {type: opencv, index_or_path: "/dev/video4", width: 1280, height: 720, fps: 30}, base: {type: opencv, index_or_path: "/dev/video2", width: 640, height: 480, fps: 30}}' \
-    --teleop.type=openarm_mini \
-    --teleop.port_left=/dev/ttyACM0 \
-    --teleop.port_right=/dev/ttyACM1 \
+    --teleop.type=bi_openarm_mini \
+    --teleop.left_arm_config.port=/dev/ttyACM0 \
+    --teleop.right_arm_config.port=/dev/ttyACM1 \
     --policy.path=outputs/pretrain/checkpoints/last/pretrained_model \
     --dataset.repo_id=your-username/rollout_hil_rtc_dataset \
     --dataset.single_task="Fold the T-shirt properly" \

docs/source/inference.mdx

@@ -117,7 +117,7 @@ lerobot-rollout \
     --strategy.num_episodes=20 \
     --policy.path=outputs/pretrain/checkpoints/last/pretrained_model \
     --robot.type=bi_openarm_follower \
-    --teleop.type=openarm_mini \
+    --teleop.type=bi_openarm_mini \
     --dataset.repo_id=${HF_USER}/rollout_hil_data \
     --dataset.single_task="Fold the T-shirt"
 ```

pyproject.toml

@@ -124,7 +124,7 @@ hardware = [
     "lerobot[deepdiff-dep]",
 ]
 viz = [
-    "rerun-sdk>=0.24.0,<0.34.0",
+    "rerun-sdk>=0.24.0,<0.27.0",
 ]
 # ── User-facing composite extras (map to CLI scripts) ─────
 # lerobot-record, lerobot-replay, lerobot-calibrate, lerobot-teleoperate, etc.

src/lerobot/datasets/sampler.py

@@ -30,6 +30,7 @@ class EpisodeAwareSampler:
         drop_n_first_frames: int = 0,
         drop_n_last_frames: int = 0,
         shuffle: bool = False,
+        generator: torch.Generator | None = None,
     ):
         """Sampler that optionally incorporates episode boundary information.
 
@@ -41,6 +42,10 @@ class EpisodeAwareSampler:
             drop_n_first_frames: Number of frames to drop from the start of each episode.
             drop_n_last_frames: Number of frames to drop from the end of each episode.
             shuffle: Whether to shuffle the indices.
+            generator: Generator used for shuffling. Exposing this attribute (even when None) lets
+                       `accelerate` register it as the synchronized RNG in distributed training, so
+                       every rank draws the same permutation and batch shards stay disjoint. When
+                       None, shuffling falls back to the global torch RNG.
         """
         if drop_n_first_frames < 0:
             raise ValueError(f"drop_n_first_frames must be >= 0, got {drop_n_first_frames}")
@@ -73,10 +78,11 @@ class EpisodeAwareSampler:
 
         self.indices = indices
         self.shuffle = shuffle
+        self.generator = generator
 
     def __iter__(self) -> Iterator[int]:
         if self.shuffle:
-            for i in torch.randperm(len(self.indices)):
+            for i in torch.randperm(len(self.indices), generator=self.generator):
                 yield self.indices[i]
         else:
             for i in self.indices:

src/lerobot/robots/bi_openarm_follower/bi_openarm_follower.py

@@ -18,7 +18,8 @@ import logging
 from functools import cached_property
 
 from lerobot.types import RobotAction, RobotObservation
-from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
+from lerobot.utils.bimanual import BimanualMixin
+from lerobot.utils.decorators import check_if_not_connected
 
 from ..openarm_follower import OpenArmFollower, OpenArmFollowerConfig
 from ..robot import Robot
@@ -27,7 +28,7 @@ from .config_bi_openarm_follower import BiOpenArmFollowerConfig
 logger = logging.getLogger(__name__)
 
 
-class BiOpenArmFollower(Robot):
+class BiOpenArmFollower(BimanualMixin, Robot):
     """
     Bimanual OpenArm Follower Arms
     """
@@ -39,15 +40,17 @@ class BiOpenArmFollower(Robot):
         super().__init__(config)
         self.config = config
 
-        # Top-level cameras are distributed evenly: each arm's OpenArmFollower
-        # will only open the cameras assigned to it. Per-arm cameras are used
-        # as fallback when top-level cameras are empty.
-        if config.cameras:
-            left_cameras = config.cameras
-            right_cameras = {}
-        else:
-            left_cameras = config.left_arm_config.cameras
-            right_cameras = config.right_arm_config.cameras
+        # Top-level cameras are opened by `left_arm` for convenience, but their
+        # keys stay unprefixed in observations (tracked via `_top_level_cam_keys`).
+        self._top_level_cam_keys = set(config.cameras)
+        _collisions = self._top_level_cam_keys & set(
+            config.left_arm_config.cameras
+        ) | self._top_level_cam_keys & set(config.right_arm_config.cameras)
+        if _collisions:
+            raise ValueError(
+                f"Top-level camera names collide with per-arm camera names: {sorted(_collisions)}"
+            )
+        left_arm_cameras = {**config.left_arm_config.cameras, **config.cameras}
 
         left_arm_config = OpenArmFollowerConfig(
             id=f"{config.id}_left" if config.id else None,
@@ -56,7 +59,7 @@ class BiOpenArmFollower(Robot):
             disable_torque_on_disconnect=config.left_arm_config.disable_torque_on_disconnect,
             use_velocity_and_torque=config.left_arm_config.use_velocity_and_torque,
             max_relative_target=config.left_arm_config.max_relative_target,
-            cameras=left_cameras,
+            cameras=left_arm_cameras,
             side=config.left_arm_config.side,
             can_interface=config.left_arm_config.can_interface,
             use_can_fd=config.left_arm_config.use_can_fd,
@@ -75,7 +78,7 @@ class BiOpenArmFollower(Robot):
             disable_torque_on_disconnect=config.right_arm_config.disable_torque_on_disconnect,
             use_velocity_and_torque=config.right_arm_config.use_velocity_and_torque,
             max_relative_target=config.right_arm_config.max_relative_target,
-            cameras=right_cameras,
+            cameras=config.right_arm_config.cameras,
             side=config.right_arm_config.side,
             can_interface=config.right_arm_config.can_interface,
             use_can_fd=config.right_arm_config.use_can_fd,
@@ -95,22 +98,19 @@ class BiOpenArmFollower(Robot):
 
     @property
     def _motors_ft(self) -> dict[str, type]:
-        left_arm_motors_ft = self.left_arm._motors_ft
-        right_arm_motors_ft = self.right_arm._motors_ft
-
-        # Right first, then left — matches the teleoperator (OpenArmMini) ordering
-        # and the dataset feature names recorded during data collection.
         return {
-            **{f"right_{k}": v for k, v in right_arm_motors_ft.items()},
-            **{f"left_{k}": v for k, v in left_arm_motors_ft.items()},
+            **{f"left_{k}": v for k, v in self.left_arm._motors_ft.items()},
+            **{f"right_{k}": v for k, v in self.right_arm._motors_ft.items()},
         }
 
     @property
     def _cameras_ft(self) -> dict[str, tuple]:
-        # Cameras already have unique user-chosen names (e.g. "left_wrist", "base",
-        # "right_wrist"), so we merge them directly — unlike motors which need the
-        # left_/right_ prefix to disambiguate identical per-arm joint names.
-        return {**self.left_arm._cameras_ft, **self.right_arm._cameras_ft}
+        out: dict[str, tuple] = {}
+        for k, v in self.left_arm._cameras_ft.items():
+            out[k if k in self._top_level_cam_keys else f"left_{k}"] = v
+        for k, v in self.right_arm._cameras_ft.items():
+            out[f"right_{k}"] = v
+        return out
 
     @cached_property
     def observation_features(self) -> dict[str, type | tuple]:
@@ -120,27 +120,6 @@ class BiOpenArmFollower(Robot):
     def action_features(self) -> dict[str, type]:
         return self._motors_ft
 
-    @property
-    def is_connected(self) -> bool:
-        return self.left_arm.is_connected and self.right_arm.is_connected
-
-    @check_if_already_connected
-    def connect(self, calibrate: bool = True) -> None:
-        self.left_arm.connect(calibrate)
-        self.right_arm.connect(calibrate)
-
-    @property
-    def is_calibrated(self) -> bool:
-        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
-
-    def calibrate(self) -> None:
-        self.left_arm.calibrate()
-        self.right_arm.calibrate()
-
-    def configure(self) -> None:
-        self.left_arm.configure()
-        self.right_arm.configure()
-
     def setup_motors(self) -> None:
         raise NotImplementedError(
             "Motor ID configuration is typically done via manufacturer tools for CAN motors."
@@ -148,21 +127,15 @@ class BiOpenArmFollower(Robot):
 
     @check_if_not_connected
     def get_observation(self) -> RobotObservation:
-        obs_dict = {}
+        obs_dict: RobotObservation = {}
 
-        # Camera keys that should NOT get the arm prefix (they already have unique names)
-        left_cam_keys = set(self.left_arm.cameras.keys())
-        right_cam_keys = set(self.right_arm.cameras.keys())
+        # Add "left_" prefix to per-arm keys; keep top-level camera keys unprefixed.
+        for key, value in self.left_arm.get_observation().items():
+            obs_dict[key if key in self._top_level_cam_keys else f"left_{key}"] = value
 
-        # Right first, then left — matches the teleoperator (OpenArmMini) ordering
-        # and the dataset feature names recorded during data collection.
-        right_obs = self.right_arm.get_observation()
-        for key, value in right_obs.items():
-            obs_dict[key if key in right_cam_keys else f"right_{key}"] = value
-
-        left_obs = self.left_arm.get_observation()
-        for key, value in left_obs.items():
-            obs_dict[key if key in left_cam_keys else f"left_{key}"] = value
+        # Add "right_" prefix
+        for key, value in self.right_arm.get_observation().items():
+            obs_dict[f"right_{key}"] = value
 
         return obs_dict
 
@@ -189,9 +162,4 @@ class BiOpenArmFollower(Robot):
         prefixed_sent_action_left = {f"left_{key}": value for key, value in sent_action_left.items()}
         prefixed_sent_action_right = {f"right_{key}": value for key, value in sent_action_right.items()}
 
-        return {**prefixed_sent_action_right, **prefixed_sent_action_left}
-
-    @check_if_not_connected
-    def disconnect(self):
-        self.left_arm.disconnect()
-        self.right_arm.disconnect()
+        return {**prefixed_sent_action_left, **prefixed_sent_action_right}

src/lerobot/robots/bi_openarm_follower/config_bi_openarm_follower.py

@@ -32,5 +32,7 @@ class BiOpenArmFollowerConfig(RobotConfig):
     left_arm_config: OpenArmFollowerConfigBase
     right_arm_config: OpenArmFollowerConfigBase
 
-    # Top-level cameras shared across both arms.
+    # Top-level cameras not attached to a specific side. Keys are kept as-is in
+    # observations (no `left_`/`right_` prefix). Per-arm cameras (declared on
+    # `{left,right}_arm_config.cameras`) are prefixed.
     cameras: dict[str, CameraConfig] = field(default_factory=dict)

src/lerobot/robots/bi_rebot_b601_follower/bi_rebot_b601_follower.py

@@ -18,7 +18,8 @@ import logging
 from functools import cached_property
 
 from lerobot.types import RobotAction, RobotObservation
-from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
+from lerobot.utils.bimanual import BimanualMixin
+from lerobot.utils.decorators import check_if_not_connected
 
 from ..rebot_b601_follower import RebotB601Follower, RebotB601FollowerRobotConfig
 from ..robot import Robot
@@ -27,7 +28,7 @@ from .config_bi_rebot_b601_follower import BiRebotB601FollowerConfig
 logger = logging.getLogger(__name__)
 
 
-class BiRebotB601Follower(Robot):
+class BiRebotB601Follower(BimanualMixin, Robot):
     """Bimanual Seeed Studio reBot B601-DM follower.
 
     Composes two single-arm :class:`RebotB601Follower` instances. Observation and
@@ -41,6 +42,18 @@ class BiRebotB601Follower(Robot):
         super().__init__(config)
         self.config = config
 
+        # Top-level cameras are opened by `left_arm` for convenience, but their
+        # keys stay unprefixed in observations (tracked via `_top_level_cam_keys`).
+        self._top_level_cam_keys = set(config.cameras)
+        _collisions = self._top_level_cam_keys & set(
+            config.left_arm_config.cameras
+        ) | self._top_level_cam_keys & set(config.right_arm_config.cameras)
+        if _collisions:
+            raise ValueError(
+                f"Top-level camera names collide with per-arm camera names: {sorted(_collisions)}"
+            )
+        left_arm_cameras = {**config.left_arm_config.cameras, **config.cameras}
+
         left_arm_config = RebotB601FollowerRobotConfig(
             id=f"{config.id}_left" if config.id else None,
             calibration_dir=config.calibration_dir,
@@ -49,7 +62,7 @@ class BiRebotB601Follower(Robot):
             dm_serial_baud=config.left_arm_config.dm_serial_baud,
             disable_torque_on_disconnect=config.left_arm_config.disable_torque_on_disconnect,
             max_relative_target=config.left_arm_config.max_relative_target,
-            cameras=config.left_arm_config.cameras,
+            cameras=left_arm_cameras,
             motor_can_ids=config.left_arm_config.motor_can_ids,
             pos_vel_velocity=config.left_arm_config.pos_vel_velocity,
             gripper_torque_ratio=config.left_arm_config.gripper_torque_ratio,
@@ -86,10 +99,12 @@ class BiRebotB601Follower(Robot):
 
     @property
     def _cameras_ft(self) -> dict[str, tuple]:
-        return {
-            **{f"left_{k}": v for k, v in self.left_arm._cameras_ft.items()},
-            **{f"right_{k}": v for k, v in self.right_arm._cameras_ft.items()},
-        }
+        out: dict[str, tuple] = {}
+        for k, v in self.left_arm._cameras_ft.items():
+            out[k if k in self._top_level_cam_keys else f"left_{k}"] = v
+        for k, v in self.right_arm._cameras_ft.items():
+            out[f"right_{k}"] = v
+        return out
 
     @cached_property
     def observation_features(self) -> dict[str, type | tuple]:
@@ -99,32 +114,13 @@ class BiRebotB601Follower(Robot):
     def action_features(self) -> dict[str, type]:
         return self._motors_ft
 
-    @property
-    def is_connected(self) -> bool:
-        return self.left_arm.is_connected and self.right_arm.is_connected
-
-    @check_if_already_connected
-    def connect(self, calibrate: bool = True) -> None:
-        self.left_arm.connect(calibrate)
-        self.right_arm.connect(calibrate)
-
-    @property
-    def is_calibrated(self) -> bool:
-        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
-
-    def calibrate(self) -> None:
-        self.left_arm.calibrate()
-        self.right_arm.calibrate()
-
-    def configure(self) -> None:
-        self.left_arm.configure()
-        self.right_arm.configure()
-
     @check_if_not_connected
     def get_observation(self) -> RobotObservation:
-        obs_dict = {}
-        obs_dict.update({f"left_{k}": v for k, v in self.left_arm.get_observation().items()})
-        obs_dict.update({f"right_{k}": v for k, v in self.right_arm.get_observation().items()})
+        obs_dict: RobotObservation = {}
+        for k, v in self.left_arm.get_observation().items():
+            obs_dict[k if k in self._top_level_cam_keys else f"left_{k}"] = v
+        for k, v in self.right_arm.get_observation().items():
+            obs_dict[f"right_{k}"] = v
         return obs_dict
 
     @check_if_not_connected
@@ -143,8 +139,3 @@ class BiRebotB601Follower(Robot):
             **{f"left_{k}": v for k, v in sent_action_left.items()},
             **{f"right_{k}": v for k, v in sent_action_right.items()},
         }
-
-    @check_if_not_connected
-    def disconnect(self) -> None:
-        self.left_arm.disconnect()
-        self.right_arm.disconnect()

src/lerobot/robots/bi_rebot_b601_follower/config_bi_rebot_b601_follower.py

@@ -14,7 +14,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from dataclasses import dataclass
+from dataclasses import dataclass, field
+
+from lerobot.cameras import CameraConfig
 
 from ..config import RobotConfig
 from ..rebot_b601_follower import RebotB601FollowerConfig
@@ -27,3 +29,8 @@ class BiRebotB601FollowerConfig(RobotConfig):
 
     left_arm_config: RebotB601FollowerConfig
     right_arm_config: RebotB601FollowerConfig
+
+    # Top-level cameras not attached to a specific side. Keys are kept as-is in
+    # observations (no `left_`/`right_` prefix). Per-arm cameras (declared on
+    # `{left,right}_arm_config.cameras`) are prefixed.
+    cameras: dict[str, CameraConfig] = field(default_factory=dict)

src/lerobot/robots/bi_so_follower/bi_so_follower.py

@@ -18,7 +18,8 @@ import logging
 from functools import cached_property
 
 from lerobot.types import RobotAction, RobotObservation
-from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
+from lerobot.utils.bimanual import BimanualMixin
+from lerobot.utils.decorators import check_if_not_connected
 
 from ..robot import Robot
 from ..so_follower import SOFollower, SOFollowerRobotConfig
@@ -27,7 +28,7 @@ from .config_bi_so_follower import BiSOFollowerConfig
 logger = logging.getLogger(__name__)
 
 
-class BiSOFollower(Robot):
+class BiSOFollower(BimanualMixin, Robot):
     """
     [Bimanual SO Follower Arms](https://github.com/TheRobotStudio/SO-ARM100) designed by TheRobotStudio
     """
@@ -39,6 +40,18 @@ class BiSOFollower(Robot):
         super().__init__(config)
         self.config = config
 
+        # Top-level cameras are opened by `left_arm` for convenience, but their
+        # keys stay unprefixed in observations (tracked via `_top_level_cam_keys`).
+        self._top_level_cam_keys = set(config.cameras)
+        _collisions = self._top_level_cam_keys & set(
+            config.left_arm_config.cameras
+        ) | self._top_level_cam_keys & set(config.right_arm_config.cameras)
+        if _collisions:
+            raise ValueError(
+                f"Top-level camera names collide with per-arm camera names: {sorted(_collisions)}"
+            )
+        left_arm_cameras = {**config.left_arm_config.cameras, **config.cameras}
+
         left_arm_config = SOFollowerRobotConfig(
             id=f"{config.id}_left" if config.id else None,
             calibration_dir=config.calibration_dir,
@@ -46,7 +59,7 @@ class BiSOFollower(Robot):
             disable_torque_on_disconnect=config.left_arm_config.disable_torque_on_disconnect,
             max_relative_target=config.left_arm_config.max_relative_target,
             use_degrees=config.left_arm_config.use_degrees,
-            cameras=config.left_arm_config.cameras,
+            cameras=left_arm_cameras,
         )
 
         right_arm_config = SOFollowerRobotConfig(
@@ -77,13 +90,12 @@ class BiSOFollower(Robot):
 
     @property
     def _cameras_ft(self) -> dict[str, tuple]:
-        left_arm_cameras_ft = self.left_arm._cameras_ft
-        right_arm_cameras_ft = self.right_arm._cameras_ft
-
-        return {
-            **{f"left_{k}": v for k, v in left_arm_cameras_ft.items()},
-            **{f"right_{k}": v for k, v in right_arm_cameras_ft.items()},
-        }
+        out: dict[str, tuple] = {}
+        for k, v in self.left_arm._cameras_ft.items():
+            out[k if k in self._top_level_cam_keys else f"left_{k}"] = v
+        for k, v in self.right_arm._cameras_ft.items():
+            out[f"right_{k}"] = v
+        return out
 
     @cached_property
     def observation_features(self) -> dict[str, type | tuple]:
@@ -93,42 +105,21 @@ class BiSOFollower(Robot):
     def action_features(self) -> dict[str, type]:
         return self._motors_ft
 
-    @property
-    def is_connected(self) -> bool:
-        return self.left_arm.is_connected and self.right_arm.is_connected
-
-    @check_if_already_connected
-    def connect(self, calibrate: bool = True) -> None:
-        self.left_arm.connect(calibrate)
-        self.right_arm.connect(calibrate)
-
-    @property
-    def is_calibrated(self) -> bool:
-        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
-
-    def calibrate(self) -> None:
-        self.left_arm.calibrate()
-        self.right_arm.calibrate()
-
-    def configure(self) -> None:
-        self.left_arm.configure()
-        self.right_arm.configure()
-
     def setup_motors(self) -> None:
         self.left_arm.setup_motors()
         self.right_arm.setup_motors()
 
     @check_if_not_connected
     def get_observation(self) -> RobotObservation:
-        obs_dict = {}
+        obs_dict: RobotObservation = {}
 
-        # Add "left_" prefix
-        left_obs = self.left_arm.get_observation()
-        obs_dict.update({f"left_{key}": value for key, value in left_obs.items()})
+        # Add "left_" prefix to per-arm keys; keep top-level camera keys unprefixed.
+        for key, value in self.left_arm.get_observation().items():
+            obs_dict[key if key in self._top_level_cam_keys else f"left_{key}"] = value
 
         # Add "right_" prefix
-        right_obs = self.right_arm.get_observation()
-        obs_dict.update({f"right_{key}": value for key, value in right_obs.items()})
+        for key, value in self.right_arm.get_observation().items():
+            obs_dict[f"right_{key}"] = value
 
         return obs_dict
 
@@ -151,8 +142,3 @@ class BiSOFollower(Robot):
         prefixed_sent_action_right = {f"right_{key}": value for key, value in sent_action_right.items()}
 
         return {**prefixed_sent_action_left, **prefixed_sent_action_right}
-
-    @check_if_not_connected
-    def disconnect(self):
-        self.left_arm.disconnect()
-        self.right_arm.disconnect()

src/lerobot/robots/bi_so_follower/config_bi_so_follower.py

@@ -14,7 +14,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from dataclasses import dataclass
+from dataclasses import dataclass, field
+
+from lerobot.cameras import CameraConfig
 
 from ..config import RobotConfig
 from ..so_follower import SOFollowerConfig
@@ -27,3 +29,8 @@ class BiSOFollowerConfig(RobotConfig):
 
     left_arm_config: SOFollowerConfig
     right_arm_config: SOFollowerConfig
+
+    # Top-level cameras not attached to a specific side. Keys are kept as-is in
+    # observations (no `left_`/`right_` prefix). Per-arm cameras (declared on
+    # `{left,right}_arm_config.cameras`) are prefixed.
+    cameras: dict[str, CameraConfig] = field(default_factory=dict)

src/lerobot/scripts/lerobot_calibrate.py

@@ -54,6 +54,7 @@ from lerobot.teleoperators import (  # noqa: F401
     Teleoperator,
     TeleoperatorConfig,
     bi_openarm_leader,
+    bi_openarm_mini,
     bi_rebot_102_leader,
     bi_so_leader,
     homunculus,

src/lerobot/scripts/lerobot_dataset_viz.py

@@ -77,21 +77,6 @@ from lerobot.utils.constants import ACTION, DONE, OBS_STATE, REWARD
 from lerobot.utils.utils import init_logging
 
 
-def get_feature_names(dataset: LeRobotDataset, key: str) -> list[str]:
-    """Return per-dimension names for a feature from the dataset metadata.
-
-    Only flat-list ``names`` metadata is used. Dict-style ``names`` and missing names fall back to ``{key}_{i}`` indices.
-    """
-    feature = dataset.features[key]
-    dim = feature["shape"][-1]
-
-    names = feature.get("names")
-    if isinstance(names, list) and len(names) == dim:
-        return [str(name) for name in names]
-
-    return [f"{key}_{d}" for d in range(dim)]
-
-
 def to_hwc_uint8_numpy(chw_float32_torch: torch.Tensor) -> np.ndarray:
     assert chw_float32_torch.dtype == torch.float32
     assert chw_float32_torch.ndim == 3
@@ -101,31 +86,6 @@ def to_hwc_uint8_numpy(chw_float32_torch: torch.Tensor) -> np.ndarray:
     return hwc_uint8_numpy
 
 
-def build_blueprint_from_dataset(dataset: LeRobotDataset):
-    """Build a Rerun blueprint laying out camera images and time series for the given dataset.
-
-    Camera images and scalar signals (action, state, reward, done, success) are arranged in a grid.
-    The per-dimension series names for ``action`` and ``state`` are applied directly
-    via blueprint overrides.
-    """
-    import rerun as rr
-    import rerun.blueprint as rrb
-
-    views = [rrb.Spatial2DView(origin=key, name=key) for key in dataset.meta.camera_keys]
-
-    # Style multi-dimensional signals (action, state) with per-dimension names.
-    for origin, key in ((ACTION, ACTION), ("state", OBS_STATE)):
-        if key in dataset.features:
-            names = get_feature_names(dataset, key)
-            styling = rr.SeriesLines(names=names)
-            views.append(rrb.TimeSeriesView(origin=origin, name=origin, overrides={origin: styling}))
-    for key in (DONE, REWARD, "next.success"):
-        if key in dataset.features:
-            views.append(rrb.TimeSeriesView(origin=key, name=key))
-
-    return rrb.Blueprint(rrb.Grid(*views))
-
-
 def visualize_dataset(
     dataset: LeRobotDataset,
     episode_index: int,
@@ -164,8 +124,7 @@ def visualize_dataset(
     import rerun as rr
 
     spawn_local_viewer = mode == "local" and not save
-    blueprint = build_blueprint_from_dataset(dataset)
-    rr.init(f"{repo_id}/episode_{episode_index}", spawn=spawn_local_viewer, default_blueprint=blueprint)
+    rr.init(f"{repo_id}/episode_{episode_index}", spawn=spawn_local_viewer)
 
     # Manually call python garbage collector after `rr.init` to avoid hanging in a blocking flush
     # when iterating on a dataloader with `num_workers` > 0
@@ -183,21 +142,26 @@ def visualize_dataset(
     for batch in tqdm.tqdm(dataloader, total=len(dataloader)):
         if first_index is None:
             first_index = batch["index"][0].item()
-
+        # iterate over the batch
         for i in range(len(batch["index"])):
             rr.set_time("frame_index", sequence=batch["index"][i].item() - first_index)
             rr.set_time("timestamp", timestamp=batch["timestamp"][i].item())
 
+            # display each camera image
             for key in dataset.meta.camera_keys:
                 img = to_hwc_uint8_numpy(batch[key][i])
                 img_entity = rr.Image(img).compress() if display_compressed_images else rr.Image(img)
                 rr.log(key, entity=img_entity)
 
+            # display each dimension of action space (e.g. actuators command)
             if ACTION in batch:
-                rr.log(ACTION, rr.Scalars(batch[ACTION][i].numpy()))
+                for dim_idx, val in enumerate(batch[ACTION][i]):
+                    rr.log(f"{ACTION}/{dim_idx}", rr.Scalars(val.item()))
 
+            # display each dimension of observed state space (e.g. agent position in joint space)
             if OBS_STATE in batch:
-                rr.log("state", rr.Scalars(batch[OBS_STATE][i].numpy()))
+                for dim_idx, val in enumerate(batch[OBS_STATE][i]):
+                    rr.log(f"state/{dim_idx}", rr.Scalars(val.item()))
 
             if DONE in batch:
                 rr.log(DONE, rr.Scalars(batch[DONE][i].item()))
@@ -209,6 +173,8 @@ def visualize_dataset(
                 rr.log("next.success", rr.Scalars(batch["next.success"][i].item()))
 
     if mode == "local" and save:
+        # save .rrd locally
+        output_dir = Path(output_dir)
         output_dir.mkdir(parents=True, exist_ok=True)
         repo_id_str = repo_id.replace("/", "_")
         rrd_path = output_dir / f"{repo_id_str}_episode_{episode_index}.rrd"
@@ -216,7 +182,7 @@ def visualize_dataset(
         return rrd_path
 
     elif mode == "distant":
-        # Keep the process alive while it serves the gRPC/web connection.
+        # stop the process from exiting since it is serving the websocket connection
         try:
             while True:
                 time.sleep(1)
@@ -331,14 +297,12 @@ def main():
         )
         logging.warning("Setting grpc_port to ws_port value.")
         kwargs["grpc_port"] = kwargs.pop("ws_port")
-    else:
-        kwargs.pop("ws_port")  # Always remove ws_port from kwargs
 
     init_logging()
     logging.info("Loading dataset")
     dataset = LeRobotDataset(repo_id, episodes=[args.episode_index], root=root, tolerance_s=tolerance_s)
 
-    visualize_dataset(dataset, **kwargs)
+    visualize_dataset(dataset, **vars(args))
 
 
 if __name__ == "__main__":

src/lerobot/scripts/lerobot_find_joint_limits.py

@@ -57,6 +57,7 @@ from lerobot.robots import (  # noqa: F401
 from lerobot.teleoperators import (  # noqa: F401
     TeleoperatorConfig,
     bi_openarm_leader,
+    bi_openarm_mini,
     bi_rebot_102_leader,
     bi_so_leader,
     gamepad,

src/lerobot/scripts/lerobot_record.py

@@ -137,6 +137,7 @@ from lerobot.teleoperators import (  # noqa: F401
     Teleoperator,
     TeleoperatorConfig,
     bi_openarm_leader,
+    bi_openarm_mini,
     bi_rebot_102_leader,
     bi_so_leader,
     homunculus,

src/lerobot/scripts/lerobot_rollout.py

@@ -174,6 +174,7 @@ from lerobot.teleoperators import (  # noqa: F401
     Teleoperator,
     TeleoperatorConfig,
     bi_openarm_leader,
+    bi_openarm_mini,
     bi_rebot_102_leader,
     bi_so_leader,
     homunculus,

src/lerobot/scripts/lerobot_setup_motors.py

@@ -41,6 +41,7 @@ from lerobot.robots import (  # noqa: F401
 )
 from lerobot.teleoperators import (  # noqa: F401
     TeleoperatorConfig,
+    bi_openarm_mini,
     bi_rebot_102_leader,
     bi_so_leader,
     koch_leader,

src/lerobot/scripts/lerobot_teleoperate.py

@@ -89,6 +89,7 @@ from lerobot.teleoperators import (  # noqa: F401
     Teleoperator,
     TeleoperatorConfig,
     bi_openarm_leader,
+    bi_openarm_mini,
     bi_rebot_102_leader,
     bi_so_leader,
     gamepad,

src/lerobot/scripts/lerobot_train.py

@@ -232,15 +232,18 @@ def train(cfg: TrainPipelineConfig, accelerator: "Accelerator | None" = None):
         torch.backends.cudnn.benchmark = True
     torch.backends.cuda.matmul.allow_tf32 = True
 
-    # Dataset loading synchronization: main process downloads first to avoid race conditions
-    if is_main_process:
-        logging.info("Creating dataset")
+    # Dataset loading synchronization: each node's local main process downloads first to avoid
+    # race conditions (the global main process only exists on node 0, so gating on it would let
+    # all ranks of the other nodes download and build the Arrow cache concurrently).
+    if accelerator.is_local_main_process:
+        if is_main_process:
+            logging.info("Creating dataset")
         dataset = make_dataset(cfg)
 
     accelerator.wait_for_everyone()
 
-    # Now all other processes can safely load the dataset
-    if not is_main_process:
+    # Now all other processes can safely load the dataset from the local cache
+    if not accelerator.is_local_main_process:
         dataset = make_dataset(cfg)
 
     # Create environment used for evaluating checkpoints during training on simulation data.
@@ -386,12 +389,19 @@ def train(cfg: TrainPipelineConfig, accelerator: "Accelerator | None" = None):
     # create dataloader for offline training
     if hasattr(active_cfg, "drop_n_last_frames"):
         shuffle = False
+        # A dedicated generator (rather than the global torch RNG) lets accelerator.prepare
+        # synchronize the shuffle permutation across ranks, keeping batch shards disjoint even
+        # when ranks consume the global RNG asymmetrically (e.g. eval on the main process only).
+        sampler_generator = torch.Generator()
+        if cfg.seed is not None:
+            sampler_generator.manual_seed(cfg.seed)
         sampler = EpisodeAwareSampler(
             dataset.meta.episodes["dataset_from_index"],
             dataset.meta.episodes["dataset_to_index"],
             episode_indices_to_use=dataset.episodes,
             drop_n_last_frames=active_cfg.drop_n_last_frames,
             shuffle=True,
+            generator=sampler_generator,
         )
     else:
         shuffle = True

src/lerobot/teleoperators/bi_openarm_leader/bi_openarm_leader.py

@@ -18,7 +18,8 @@ import logging
 from functools import cached_property
 
 from lerobot.types import RobotAction
-from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
+from lerobot.utils.bimanual import BimanualMixin
+from lerobot.utils.decorators import check_if_not_connected
 
 from ..openarm_leader import OpenArmLeader, OpenArmLeaderConfig
 from ..teleoperator import Teleoperator
@@ -27,7 +28,7 @@ from .config_bi_openarm_leader import BiOpenArmLeaderConfig
 logger = logging.getLogger(__name__)
 
 
-class BiOpenArmLeader(Teleoperator):
+class BiOpenArmLeader(BimanualMixin, Teleoperator):
     """
     Bimanual OpenArm Leader Arms
     """
@@ -86,27 +87,6 @@ class BiOpenArmLeader(Teleoperator):
     def feedback_features(self) -> dict[str, type]:
         return {}
 
-    @property
-    def is_connected(self) -> bool:
-        return self.left_arm.is_connected and self.right_arm.is_connected
-
-    @check_if_already_connected
-    def connect(self, calibrate: bool = True) -> None:
-        self.left_arm.connect(calibrate)
-        self.right_arm.connect(calibrate)
-
-    @property
-    def is_calibrated(self) -> bool:
-        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
-
-    def calibrate(self) -> None:
-        self.left_arm.calibrate()
-        self.right_arm.calibrate()
-
-    def configure(self) -> None:
-        self.left_arm.configure()
-        self.right_arm.configure()
-
     def setup_motors(self) -> None:
         raise NotImplementedError(
             "Motor ID configuration is typically done via manufacturer tools for CAN motors."
@@ -129,8 +109,3 @@ class BiOpenArmLeader(Teleoperator):
     def send_feedback(self, feedback: dict[str, float]) -> None:
         # TODO: Implement force feedback
         raise NotImplementedError
-
-    @check_if_not_connected
-    def disconnect(self) -> None:
-        self.left_arm.disconnect()
-        self.right_arm.disconnect()

src/lerobot/teleoperators/bi_openarm_leader/config_bi_openarm_leader.py

@@ -23,7 +23,7 @@ from ..openarm_leader import OpenArmLeaderConfigBase
 @TeleoperatorConfig.register_subclass("bi_openarm_leader")
 @dataclass
 class BiOpenArmLeaderConfig(TeleoperatorConfig):
-    """Configuration class for Bi OpenArm Follower robots."""
+    """Configuration class for Bi OpenArm Leader teleoperators."""
 
     left_arm_config: OpenArmLeaderConfigBase
     right_arm_config: OpenArmLeaderConfigBase

src/lerobot/teleoperators/bi_openarm_mini/__init__.py

@@ -0,0 +1,20 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from .bi_openarm_mini import BiOpenArmMini
+from .config_bi_openarm_mini import BiOpenArmMiniConfig
+
+__all__ = ["BiOpenArmMini", "BiOpenArmMiniConfig"]

src/lerobot/teleoperators/bi_openarm_mini/bi_openarm_mini.py

@@ -0,0 +1,101 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+from functools import cached_property
+
+from lerobot.types import RobotAction
+from lerobot.utils.bimanual import BimanualMixin
+from lerobot.utils.decorators import check_if_not_connected
+
+from ..openarm_mini import OpenArmMini, OpenArmMiniConfig
+from ..teleoperator import Teleoperator
+from .config_bi_openarm_mini import BiOpenArmMiniConfig
+
+logger = logging.getLogger(__name__)
+
+
+class BiOpenArmMini(BimanualMixin, Teleoperator):
+    """Bimanual OpenArm Mini teleoperator.
+
+    Composes two single-arm :class:`OpenArmMini` instances. Action and feedback
+    keys of each arm are namespaced with a ``left_`` / ``right_`` prefix, so a
+    bimanual leader can teleoperate a bimanual OpenArm follower.
+    """
+
+    config_class = BiOpenArmMiniConfig
+    name = "bi_openarm_mini"
+
+    def __init__(self, config: BiOpenArmMiniConfig):
+        super().__init__(config)
+        self.config = config
+
+        # `side` is forced to match left/right regardless of what the user passed
+        # on the per-arm base config — the bimanual wrapper owns the side semantics.
+        left_arm_config = OpenArmMiniConfig(
+            id=f"{config.id}_left" if config.id else None,
+            calibration_dir=config.calibration_dir,
+            port=config.left_arm_config.port,
+            side="left",
+            use_degrees=config.left_arm_config.use_degrees,
+        )
+
+        right_arm_config = OpenArmMiniConfig(
+            id=f"{config.id}_right" if config.id else None,
+            calibration_dir=config.calibration_dir,
+            port=config.right_arm_config.port,
+            side="right",
+            use_degrees=config.right_arm_config.use_degrees,
+        )
+
+        self.left_arm = OpenArmMini(left_arm_config)
+        self.right_arm = OpenArmMini(right_arm_config)
+
+    @cached_property
+    def action_features(self) -> dict[str, type]:
+        return {
+            **{f"left_{k}": v for k, v in self.left_arm.action_features.items()},
+            **{f"right_{k}": v for k, v in self.right_arm.action_features.items()},
+        }
+
+    @cached_property
+    def feedback_features(self) -> dict[str, type]:
+        return {
+            **{f"left_{k}": v for k, v in self.left_arm.feedback_features.items()},
+            **{f"right_{k}": v for k, v in self.right_arm.feedback_features.items()},
+        }
+
+    def setup_motors(self) -> None:
+        self.left_arm.setup_motors()
+        self.right_arm.setup_motors()
+
+    @check_if_not_connected
+    def get_action(self) -> RobotAction:
+        action: RobotAction = {}
+        for k, v in self.left_arm.get_action().items():
+            action[f"left_{k}"] = v
+        for k, v in self.right_arm.get_action().items():
+            action[f"right_{k}"] = v
+        return action
+
+    @check_if_not_connected
+    def send_feedback(self, feedback: dict[str, float]) -> None:
+        left_fb = {k.removeprefix("left_"): v for k, v in feedback.items() if k.startswith("left_")}
+        right_fb = {k.removeprefix("right_"): v for k, v in feedback.items() if k.startswith("right_")}
+        if left_fb:
+            self.left_arm.send_feedback(left_fb)
+        if right_fb:
+            self.right_arm.send_feedback(right_fb)

src/lerobot/teleoperators/bi_openarm_mini/config_bi_openarm_mini.py

@@ -0,0 +1,29 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from dataclasses import dataclass
+
+from ..config import TeleoperatorConfig
+from ..openarm_mini import OpenArmMiniConfigBase
+
+
+@TeleoperatorConfig.register_subclass("bi_openarm_mini")
+@dataclass
+class BiOpenArmMiniConfig(TeleoperatorConfig):
+    """Configuration class for Bi OpenArm Mini teleoperators."""
+
+    left_arm_config: OpenArmMiniConfigBase
+    right_arm_config: OpenArmMiniConfigBase

src/lerobot/teleoperators/bi_rebot_102_leader/__init__.py

@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .bi_rebot_102_leader import BiRebotArm102Leader
-from .config_bi_rebot_102_leader import BiRebotArm102LeaderConfig
+from .bi_rebot_102_leader import BiRebot102Leader
+from .config_bi_rebot_102_leader import BiRebot102LeaderConfig
 
-__all__ = ["BiRebotArm102Leader", "BiRebotArm102LeaderConfig"]
+__all__ = ["BiRebot102Leader", "BiRebot102LeaderConfig"]

src/lerobot/teleoperators/bi_rebot_102_leader/bi_rebot_102_leader.py

@@ -18,16 +18,17 @@ import logging
 from functools import cached_property
 
 from lerobot.types import RobotAction
-from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
+from lerobot.utils.bimanual import BimanualMixin
+from lerobot.utils.decorators import check_if_not_connected
 
 from ..rebot_102_leader import RebotArm102Leader, RebotArm102LeaderTeleopConfig
 from ..teleoperator import Teleoperator
-from .config_bi_rebot_102_leader import BiRebotArm102LeaderConfig
+from .config_bi_rebot_102_leader import BiRebot102LeaderConfig
 
 logger = logging.getLogger(__name__)
 
 
-class BiRebotArm102Leader(Teleoperator):
+class BiRebot102Leader(BimanualMixin, Teleoperator):
     """Bimanual Seeed Studio StarArm102 / reBot Arm 102 leader.
 
     Composes two single-arm :class:`RebotArm102Leader` instances. Action keys of
@@ -35,10 +36,10 @@ class BiRebotArm102Leader(Teleoperator):
     leader can teleoperate a bimanual reBot B601 follower.
     """
 
-    config_class = BiRebotArm102LeaderConfig
+    config_class = BiRebot102LeaderConfig
     name = "bi_rebot_102_leader"
 
-    def __init__(self, config: BiRebotArm102LeaderConfig):
+    def __init__(self, config: BiRebot102LeaderConfig):
         super().__init__(config)
         self.config = config
 
@@ -76,27 +77,6 @@ class BiRebotArm102Leader(Teleoperator):
     def feedback_features(self) -> dict[str, type]:
         return {}
 
-    @property
-    def is_connected(self) -> bool:
-        return self.left_arm.is_connected and self.right_arm.is_connected
-
-    @check_if_already_connected
-    def connect(self, calibrate: bool = True) -> None:
-        self.left_arm.connect(calibrate)
-        self.right_arm.connect(calibrate)
-
-    @property
-    def is_calibrated(self) -> bool:
-        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
-
-    def calibrate(self) -> None:
-        self.left_arm.calibrate()
-        self.right_arm.calibrate()
-
-    def configure(self) -> None:
-        self.left_arm.configure()
-        self.right_arm.configure()
-
     @check_if_not_connected
     def get_action(self) -> RobotAction:
         action_dict = {}
@@ -106,8 +86,3 @@ class BiRebotArm102Leader(Teleoperator):
 
     def send_feedback(self, feedback: dict[str, float]) -> None:
         raise NotImplementedError("Feedback is not implemented for the reBot Arm 102 leader.")
-
-    @check_if_not_connected
-    def disconnect(self) -> None:
-        self.left_arm.disconnect()
-        self.right_arm.disconnect()

src/lerobot/teleoperators/bi_rebot_102_leader/config_bi_rebot_102_leader.py

@@ -22,7 +22,7 @@ from ..rebot_102_leader import RebotArm102LeaderConfig
 
 @TeleoperatorConfig.register_subclass("bi_rebot_102_leader")
 @dataclass
-class BiRebotArm102LeaderConfig(TeleoperatorConfig):
+class BiRebot102LeaderConfig(TeleoperatorConfig):
     """Configuration class for the bimanual reBot Arm 102 leader teleoperator."""
 
     left_arm_config: RebotArm102LeaderConfig

src/lerobot/teleoperators/bi_so_leader/bi_so_leader.py

@@ -17,7 +17,9 @@
 import logging
 from functools import cached_property
 
-from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
+from lerobot.types import RobotAction
+from lerobot.utils.bimanual import BimanualMixin
+from lerobot.utils.decorators import check_if_not_connected
 
 from ..so_leader import SOLeader, SOLeaderTeleopConfig
 from ..teleoperator import Teleoperator
@@ -26,7 +28,7 @@ from .config_bi_so_leader import BiSOLeaderConfig
 logger = logging.getLogger(__name__)
 
 
-class BiSOLeader(Teleoperator):
+class BiSOLeader(BimanualMixin, Teleoperator):
     """
     [Bimanual SO Leader Arms](https://github.com/TheRobotStudio/SO-ARM100) designed by TheRobotStudio
     """
@@ -67,33 +69,12 @@ class BiSOLeader(Teleoperator):
     def feedback_features(self) -> dict[str, type]:
         return {}
 
-    @property
-    def is_connected(self) -> bool:
-        return self.left_arm.is_connected and self.right_arm.is_connected
-
-    @check_if_already_connected
-    def connect(self, calibrate: bool = True) -> None:
-        self.left_arm.connect(calibrate)
-        self.right_arm.connect(calibrate)
-
-    @property
-    def is_calibrated(self) -> bool:
-        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
-
-    def calibrate(self) -> None:
-        self.left_arm.calibrate()
-        self.right_arm.calibrate()
-
-    def configure(self) -> None:
-        self.left_arm.configure()
-        self.right_arm.configure()
-
     def setup_motors(self) -> None:
         self.left_arm.setup_motors()
         self.right_arm.setup_motors()
 
     @check_if_not_connected
-    def get_action(self) -> dict[str, float]:
+    def get_action(self) -> RobotAction:
         action_dict = {}
 
         # Add "left_" prefix
@@ -109,8 +90,3 @@ class BiSOLeader(Teleoperator):
     def send_feedback(self, feedback: dict[str, float]) -> None:
         # TODO: Implement force feedback
         raise NotImplementedError
-
-    @check_if_not_connected
-    def disconnect(self) -> None:
-        self.left_arm.disconnect()
-        self.right_arm.disconnect()

src/lerobot/teleoperators/openarm_mini/__init__.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 
-# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .config_openarm_mini import OpenArmMiniConfig
+from .config_openarm_mini import OpenArmMiniConfig, OpenArmMiniConfigBase
 from .openarm_mini import OpenArmMini
 
-__all__ = ["OpenArmMini", "OpenArmMiniConfig"]
+__all__ = ["OpenArmMini", "OpenArmMiniConfig", "OpenArmMiniConfigBase"]

src/lerobot/teleoperators/openarm_mini/config_openarm_mini.py

@@ -19,12 +19,21 @@ from dataclasses import dataclass
 from ..config import TeleoperatorConfig
 
 
-@TeleoperatorConfig.register_subclass("openarm_mini")
 @dataclass
-class OpenArmMiniConfig(TeleoperatorConfig):
-    """Configuration for OpenArm Mini teleoperator with Feetech motors (dual arms)."""
+class OpenArmMiniConfigBase:
+    """Base configuration for the OpenArm Mini teleoperator (Feetech STS3215, 7DOF + gripper)."""
 
-    port_right: str = "/dev/ttyUSB0"
-    port_left: str = "/dev/ttyUSB1"
+    # Serial port for the Feetech bus (e.g., "/dev/ttyUSB0").
+    port: str
+
+    # Side of the arm: "left" or "right". Controls per-joint direction flips applied
+    # during readout. If `None`, no flipping is applied.
+    side: str | None = None
 
     use_degrees: bool = True
+
+
+@TeleoperatorConfig.register_subclass("openarm_mini")
+@dataclass
+class OpenArmMiniConfig(TeleoperatorConfig, OpenArmMiniConfigBase):
+    pass

src/lerobot/teleoperators/openarm_mini/openarm_mini.py

@@ -31,22 +31,22 @@ from .config_openarm_mini import OpenArmMiniConfig
 
 logger = logging.getLogger(__name__)
 
-# Motors whose direction is inverted during readout
-RIGHT_MOTORS_TO_FLIP = ["joint_1", "joint_2", "joint_3", "joint_4", "joint_5", "joint_7"]
-LEFT_MOTORS_TO_FLIP = ["joint_1", "joint_3", "joint_4", "joint_5", "joint_6", "joint_7"]
+# Per-side motor direction flips applied during readout.
+SIDE_MOTORS_TO_FLIP: dict[str, list[str]] = {
+    "left": ["joint_1", "joint_3", "joint_4", "joint_5", "joint_6", "joint_7"],
+    "right": ["joint_1", "joint_2", "joint_3", "joint_4", "joint_5", "joint_7"],
+}
 
-# Leader joint 6 maps to follower joint 7 and vice versa
+# Leader joint 6 ↔ follower joint 7 (symmetric — its own inverse).
 JOINT_REMAP = {"joint_6": "joint_7", "joint_7": "joint_6"}
-JOINT_REMAP_REVERSE = {"joint_7": "joint_6", "joint_6": "joint_7"}
 
 GRIPPER_TELEOP_TO_DEGREES = -0.65
 
 
 class OpenArmMini(Teleoperator):
-    """
-    OpenArm Mini Teleoperator with dual Feetech-based arms (8 motors per arm).
+    """OpenArm Mini single-arm teleoperator (Feetech STS3215, 7DOF + gripper).
 
-    Each arm has 7 joints plus a gripper, using Feetech STS3215 servos.
+    For the bimanual setup, see :class:`BiOpenArmMini` which composes two of these.
     """
 
     config_class = OpenArmMiniConfig
@@ -56,9 +56,12 @@ class OpenArmMini(Teleoperator):
         super().__init__(config)
         self.config = config
 
+        if config.side is not None and config.side not in SIDE_MOTORS_TO_FLIP:
+            raise ValueError(f"Invalid side '{config.side}'; expected 'left', 'right', or None.")
+        self._motors_to_flip: list[str] = SIDE_MOTORS_TO_FLIP.get(config.side, []) if config.side else []
+
         norm_mode_body = MotorNormMode.DEGREES
-
-        motors_right = {
+        motors = {
             "joint_1": Motor(1, "sts3215", norm_mode_body),
             "joint_2": Motor(2, "sts3215", norm_mode_body),
             "joint_3": Motor(3, "sts3215", norm_mode_body),
@@ -69,46 +72,15 @@ class OpenArmMini(Teleoperator):
             "gripper": Motor(8, "sts3215", MotorNormMode.RANGE_0_100),
         }
 
-        motors_left = {
-            "joint_1": Motor(1, "sts3215", norm_mode_body),
-            "joint_2": Motor(2, "sts3215", norm_mode_body),
-            "joint_3": Motor(3, "sts3215", norm_mode_body),
-            "joint_4": Motor(4, "sts3215", norm_mode_body),
-            "joint_5": Motor(5, "sts3215", norm_mode_body),
-            "joint_6": Motor(6, "sts3215", norm_mode_body),
-            "joint_7": Motor(7, "sts3215", norm_mode_body),
-            "gripper": Motor(8, "sts3215", MotorNormMode.RANGE_0_100),
-        }
-
-        cal_right = {
-            k.replace("right_", ""): v for k, v in (self.calibration or {}).items() if k.startswith("right_")
-        }
-        cal_left = {
-            k.replace("left_", ""): v for k, v in (self.calibration or {}).items() if k.startswith("left_")
-        }
-
-        self.bus_right = FeetechMotorsBus(
-            port=self.config.port_right,
-            motors=motors_right,
-            calibration=cal_right,
-        )
-
-        self.bus_left = FeetechMotorsBus(
-            port=self.config.port_left,
-            motors=motors_left,
-            calibration=cal_left,
+        self.bus = FeetechMotorsBus(
+            port=self.config.port,
+            motors=motors,
+            calibration=self.calibration,
         )
 
     @property
     def action_features(self) -> dict[str, type]:
-        # Right first, then left — matches the robot (BiOpenArmFollower) ordering
-        # and the dataset feature names recorded during data collection.
-        features: dict[str, type] = {}
-        for motor in self.bus_right.motors:
-            features[f"right_{motor}.pos"] = float
-        for motor in self.bus_left.motors:
-            features[f"left_{motor}.pos"] = float
-        return features
+        return {f"{motor}.pos": float for motor in self.bus.motors}
 
     @property
     def feedback_features(self) -> dict[str, type]:
@@ -116,14 +88,12 @@ class OpenArmMini(Teleoperator):
 
     @property
     def is_connected(self) -> bool:
-        return self.bus_right.is_connected and self.bus_left.is_connected
+        return self.bus.is_connected
 
     @check_if_already_connected
     def connect(self, calibrate: bool = True) -> None:
-        logger.info(f"Connecting right arm on {self.config.port_right}...")
-        self.bus_right.connect()
-        logger.info(f"Connecting left arm on {self.config.port_left}...")
-        self.bus_left.connect()
+        logger.info(f"Connecting arm on {self.config.port}...")
+        self.bus.connect()
 
         if calibrate:
             self.calibrate()
@@ -133,14 +103,14 @@ class OpenArmMini(Teleoperator):
 
     @property
     def is_calibrated(self) -> bool:
-        return self.bus_right.is_calibrated and self.bus_left.is_calibrated
+        return self.bus.is_calibrated
 
     def calibrate(self) -> None:
         """
-        Run calibration procedure for OpenArm Mini.
+        Run calibration procedure for a single OpenArm Mini arm.
 
         1. Disable torque
-        2. Ask user to position arms in hanging position with grippers closed
+        2. Ask user to position arm in hanging position with gripper closed
         3. Set this as zero position via half-turn homing
         4. Interactive gripper calibration (open/close positions)
         5. Save calibration
@@ -152,70 +122,51 @@ class OpenArmMini(Teleoperator):
             )
             if user_input.strip().lower() != "c":
                 logger.info(f"Using existing calibration for {self.id}")
-                cal_right = {
-                    k.replace("right_", ""): v for k, v in self.calibration.items() if k.startswith("right_")
-                }
-                cal_left = {
-                    k.replace("left_", ""): v for k, v in self.calibration.items() if k.startswith("left_")
-                }
-                self.bus_right.write_calibration(cal_right)
-                self.bus_left.write_calibration(cal_left)
+                self.bus.write_calibration(self.calibration)
                 return
 
         logger.info(f"\nRunning calibration for {self}")
 
-        self._calibrate_arm("right", self.bus_right)
-        self._calibrate_arm("left", self.bus_left)
+        self.bus.disable_torque()
 
-        self._save_calibration()
-        print(f"\nCalibration complete and saved to {self.calibration_fpath}")
+        logger.info("Setting Phase to 12 for all motors...")
+        for motor in self.bus.motors:
+            self.bus.write("Phase", motor, 12)
 
-    def _calibrate_arm(self, arm_name: str, bus: FeetechMotorsBus) -> None:
-        """Calibrate a single arm with Feetech motors."""
-        logger.info(f"\n=== Calibrating {arm_name.upper()} arm ===")
-
-        bus.disable_torque()
-
-        logger.info(f"Setting Phase to 12 for all motors in {arm_name.upper()} arm...")
-        for motor in bus.motors:
-            bus.write("Phase", motor, 12)
-
-        for motor in bus.motors:
-            bus.write("Operating_Mode", motor, OperatingMode.POSITION.value)
+        for motor in self.bus.motors:
+            self.bus.write("Operating_Mode", motor, OperatingMode.POSITION.value)
 
         input(
-            f"\nCalibration: Zero Position ({arm_name.upper()} arm)\n"
+            "\nCalibration: Zero Position\n"
             "Position the arm in the following configuration:\n"
             "  - Arm hanging straight down\n"
             "  - Gripper closed\n"
             "Press ENTER when ready..."
         )
 
-        homing_offsets = bus.set_half_turn_homings()
-        logger.info(f"{arm_name.capitalize()} arm zero position set.")
+        homing_offsets = self.bus.set_half_turn_homings()
+        logger.info("Arm zero position set.")
 
-        print(f"\nSetting motor ranges for {arm_name.upper()} arm\n")
+        print("\nSetting motor ranges\n")
 
         if self.calibration is None:
             self.calibration = {}
 
-        motor_resolution = bus.model_resolution_table[list(bus.motors.values())[0].model]
+        motor_resolution = self.bus.model_resolution_table[list(self.bus.motors.values())[0].model]
         max_res = motor_resolution - 1
 
-        for motor_name, motor in bus.motors.items():
-            prefixed_name = f"{arm_name}_{motor_name}"
-
+        for motor_name, motor in self.bus.motors.items():
             if motor_name == "gripper":
                 input(
-                    f"\nGripper Calibration ({arm_name.upper()} arm)\n"
-                    f"Step 1: CLOSE the gripper fully\n"
-                    f"Press ENTER when gripper is closed..."
+                    "\nGripper Calibration\n"
+                    "Step 1: CLOSE the gripper fully\n"
+                    "Press ENTER when gripper is closed..."
                 )
-                closed_pos = bus.read("Present_Position", motor_name, normalize=False)
+                closed_pos = self.bus.read("Present_Position", motor_name, normalize=False)
                 logger.info(f"  Gripper closed position recorded: {closed_pos}")
 
                 input("\nStep 2: OPEN the gripper fully\nPress ENTER when gripper is fully open...")
-                open_pos = bus.read("Present_Position", motor_name, normalize=False)
+                open_pos = self.bus.read("Present_Position", motor_name, normalize=False)
                 logger.info(f"  Gripper open position recorded: {open_pos}")
 
                 if closed_pos < open_pos:
@@ -228,16 +179,16 @@ class OpenArmMini(Teleoperator):
                     drive_mode = 1
 
                 logger.info(
-                    f"  {prefixed_name}: range set to [{range_min}, {range_max}] "
+                    f"  {motor_name}: range set to [{range_min}, {range_max}] "
                     f"(0=closed, 100=open, drive_mode={drive_mode})"
                 )
             else:
                 range_min = 0
                 range_max = max_res
                 drive_mode = 0
-                logger.info(f"  {prefixed_name}: range set to [0, {max_res}] (full motor range)")
+                logger.info(f"  {motor_name}: range set to [0, {max_res}] (full motor range)")
 
-            self.calibration[prefixed_name] = MotorCalibration(
+            self.calibration[motor_name] = MotorCalibration(
                 id=motor.id,
                 drive_mode=drive_mode,
                 homing_offset=homing_offsets[motor_name],
@@ -245,108 +196,68 @@ class OpenArmMini(Teleoperator):
                 range_max=range_max,
             )
 
-        cal_for_bus = {
-            k.replace(f"{arm_name}_", ""): v
-            for k, v in self.calibration.items()
-            if k.startswith(f"{arm_name}_")
-        }
-        bus.write_calibration(cal_for_bus)
+        self.bus.write_calibration(self.calibration)
+        self._save_calibration()
+        print(f"\nCalibration complete and saved to {self.calibration_fpath}")
 
     def configure(self) -> None:
-        self.bus_right.disable_torque()
-        self.bus_right.configure_motors()
-        for motor in self.bus_right.motors:
-            self.bus_right.write("Operating_Mode", motor, OperatingMode.POSITION.value)
-
-        self.bus_left.disable_torque()
-        self.bus_left.configure_motors()
-        for motor in self.bus_left.motors:
-            self.bus_left.write("Operating_Mode", motor, OperatingMode.POSITION.value)
+        self.bus.disable_torque()
+        self.bus.configure_motors()
+        for motor in self.bus.motors:
+            self.bus.write("Operating_Mode", motor, OperatingMode.POSITION.value)
 
     def setup_motors(self) -> None:
-        print("\nSetting up RIGHT arm motors...")
-        for motor in reversed(self.bus_right.motors):
-            input(f"Connect the controller board to the RIGHT '{motor}' motor only and press enter.")
-            self.bus_right.setup_motor(motor)
-            print(f"RIGHT '{motor}' motor id set to {self.bus_right.motors[motor].id}")
-
-        print("\nSetting up LEFT arm motors...")
-        for motor in reversed(self.bus_left.motors):
-            input(f"Connect the controller board to the LEFT '{motor}' motor only and press enter.")
-            self.bus_left.setup_motor(motor)
-            print(f"LEFT '{motor}' motor id set to {self.bus_left.motors[motor].id}")
+        for motor in reversed(self.bus.motors):
+            input(f"Connect the controller board to the '{motor}' motor only and press enter.")
+            self.bus.setup_motor(motor)
+            print(f"'{motor}' motor id set to {self.bus.motors[motor].id}")
 
     @check_if_not_connected
     def get_action(self) -> RobotAction:
-        """Get current action from both arms (read positions from all motors)."""
+        """Get current action (read positions from all motors)."""
         start = time.perf_counter()
 
-        right_positions = self.bus_right.sync_read("Present_Position")
-        left_positions = self.bus_left.sync_read("Present_Position")
+        positions = self.bus.sync_read("Present_Position")
 
-        # Right first, then left — matches the robot (BiOpenArmFollower) ordering
-        # and the dataset feature names recorded during data collection.
         # Joint 6↔7 remap: leader joint_6 → follower joint_7 and vice versa.
+        # Per-side direction flip is applied based on the configured `side`.
         action: dict[str, Any] = {}
-        for motor, val in right_positions.items():
+        for motor, val in positions.items():
             target = JOINT_REMAP.get(motor, motor)
             if motor == "gripper":
                 # Convert gripper from teleop 0-100 to openarms degrees: 0→0°, 100→-65°
-                action[f"right_{target}.pos"] = val * GRIPPER_TELEOP_TO_DEGREES
+                action[f"{target}.pos"] = val * GRIPPER_TELEOP_TO_DEGREES
             else:
-                action[f"right_{target}.pos"] = -val if motor in RIGHT_MOTORS_TO_FLIP else val
-        for motor, val in left_positions.items():
-            target = JOINT_REMAP.get(motor, motor)
-            if motor == "gripper":
-                action[f"left_{target}.pos"] = val * GRIPPER_TELEOP_TO_DEGREES
-            else:
-                action[f"left_{target}.pos"] = -val if motor in LEFT_MOTORS_TO_FLIP else val
+                action[f"{target}.pos"] = -val if motor in self._motors_to_flip else val
 
         dt_ms = (time.perf_counter() - start) * 1e3
         logger.debug(f"{self} read action: {dt_ms:.1f}ms")
         return action
 
     def enable_torque(self) -> None:
-        """Enable torque on both arms for position control."""
-        self.bus_right.enable_torque()
-        self.bus_left.enable_torque()
+        self.bus.enable_torque()
 
     def disable_torque(self) -> None:
-        """Disable torque on both arms for free movement."""
-        self.bus_right.disable_torque()
-        self.bus_left.disable_torque()
+        self.bus.disable_torque()
 
     def write_goal_positions(self, positions: dict[str, float]) -> None:
         """Write goal positions to motors (inverse of get_action flip/gripper/remap logic)."""
-        right_goals: dict[str, float] = {}
-        left_goals: dict[str, float] = {}
-
+        goals: dict[str, float] = {}
         for key, val in positions.items():
             if not key.endswith(".pos"):
                 continue
-            motor_name = key.removesuffix(".pos")
-            if motor_name.startswith("right_"):
-                base = motor_name.removeprefix("right_")
-                # Reverse remap: follower joint_7 → leader joint_6 and vice versa
-                target = JOINT_REMAP_REVERSE.get(base, base)
-                if base == "gripper":
-                    # Convert robot degrees to teleop 0-100: 0°→0, -65°→100
-                    right_goals[target] = val / GRIPPER_TELEOP_TO_DEGREES
-                else:
-                    # Un-flip using the ORIGINAL motor name (target = leader motor)
-                    right_goals[target] = -val if target in RIGHT_MOTORS_TO_FLIP else val
-            elif motor_name.startswith("left_"):
-                base = motor_name.removeprefix("left_")
-                target = JOINT_REMAP_REVERSE.get(base, base)
-                if base == "gripper":
-                    left_goals[target] = val / GRIPPER_TELEOP_TO_DEGREES
-                else:
-                    left_goals[target] = -val if target in LEFT_MOTORS_TO_FLIP else val
+            base = key.removesuffix(".pos")
+            # JOINT_REMAP is symmetric (its own inverse).
+            target = JOINT_REMAP.get(base, base)
+            if base == "gripper":
+                # Convert robot degrees to teleop 0-100: 0°→0, -65°→100
+                goals[target] = val / GRIPPER_TELEOP_TO_DEGREES
+            else:
+                # Un-flip using the ORIGINAL motor name (target = leader motor)
+                goals[target] = -val if target in self._motors_to_flip else val
 
-        if right_goals:
-            self.bus_right.sync_write("Goal_Position", right_goals)
-        if left_goals:
-            self.bus_left.sync_write("Goal_Position", left_goals)
+        if goals:
+            self.bus.sync_write("Goal_Position", goals)
 
     @check_if_not_connected
     def send_feedback(self, feedback: dict[str, float]) -> None:
@@ -354,6 +265,5 @@ class OpenArmMini(Teleoperator):
 
     @check_if_not_connected
     def disconnect(self) -> None:
-        self.bus_right.disconnect()
-        self.bus_left.disconnect()
+        self.bus.disconnect()
         logger.info(f"{self} disconnected.")

src/lerobot/teleoperators/utils.py

@@ -99,14 +99,18 @@ def make_teleoperator_from_config(config: TeleoperatorConfig) -> "Teleoperator":
         from .openarm_mini import OpenArmMini
 
         return OpenArmMini(config)
+    elif config.type == "bi_openarm_mini":
+        from .bi_openarm_mini import BiOpenArmMini
+
+        return BiOpenArmMini(config)
     elif config.type == "rebot_102_leader":
         from .rebot_102_leader import RebotArm102Leader
 
         return RebotArm102Leader(config)
     elif config.type == "bi_rebot_102_leader":
-        from .bi_rebot_102_leader import BiRebotArm102Leader
+        from .bi_rebot_102_leader import BiRebot102Leader
 
-        return BiRebotArm102Leader(config)
+        return BiRebot102Leader(config)
     else:
         try:
             return cast("Teleoperator", make_device_from_device_class(config))

src/lerobot/utils/bimanual.py

@@ -0,0 +1,63 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from typing import Any
+
+from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
+
+
+class BimanualMixin:
+    """Lifecycle delegation for bimanual robots and teleoperators.
+
+    Concrete subclasses must populate ``self.left_arm`` and ``self.right_arm`` in
+    their own ``__init__``. They retain ownership of feature dicts and the
+    data-routing methods (``get_action`` / ``send_action`` / ``get_observation`` /
+    ``send_feedback``), which vary per-embodiment.
+
+    Inherit before the ``Robot`` / ``Teleoperator`` base so the mixin's methods
+    take precedence in the MRO::
+
+        class BiFooFollower(BimanualMixin, Robot): ...
+    """
+
+    left_arm: Any
+    right_arm: Any
+
+    @property
+    def is_connected(self) -> bool:
+        return self.left_arm.is_connected and self.right_arm.is_connected
+
+    @property
+    def is_calibrated(self) -> bool:
+        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
+
+    @check_if_already_connected
+    def connect(self, calibrate: bool = True) -> None:
+        self.left_arm.connect(calibrate)
+        self.right_arm.connect(calibrate)
+
+    def calibrate(self) -> None:
+        self.left_arm.calibrate()
+        self.right_arm.calibrate()
+
+    def configure(self) -> None:
+        self.left_arm.configure()
+        self.right_arm.configure()
+
+    @check_if_not_connected
+    def disconnect(self) -> None:
+        self.left_arm.disconnect()
+        self.right_arm.disconnect()

src/lerobot/utils/visualization_utils.py

@@ -38,8 +38,6 @@ def init_rerun(
     require_package("rerun-sdk", extra="viz", import_name="rerun")
     import rerun as rr
 
-    log_rerun_data.blueprint = None  # Reset blueprint cache for new session
-
     batch_size = os.getenv("RERUN_FLUSH_NUM_BYTES", "8000")
     os.environ["RERUN_FLUSH_NUM_BYTES"] = batch_size
     rr.init(session_name)
@@ -65,38 +63,6 @@ def _is_scalar(x):
     )
 
 
-def _build_blueprint(observation_paths: set[str], action_paths: set[str], image_paths: set[str]):
-    """Build a Rerun blueprint laying out camera images, observation and action scalars in separate views.
-
-    Camera images, observation and action scalars are arranged in a grid.
-    """
-
-    # Safe + zero-overhead: `log_rerun_data` already ran the `require_package` guard and imported rerun.
-    import rerun.blueprint as rrb
-
-    views = [rrb.Spatial2DView(origin=path, name=path) for path in sorted(image_paths)]
-
-    if observation_paths:
-        views.append(rrb.TimeSeriesView(name="observation", contents=sorted(observation_paths)))
-    if action_paths:
-        views.append(rrb.TimeSeriesView(name="action", contents=sorted(action_paths)))
-
-    return rrb.Blueprint(rrb.Grid(*views))
-
-
-def _ensure_blueprint(observation_paths: set[str], action_paths: set[str], image_paths: set[str]) -> None:
-    """Build and send the blueprint once, from the first observation and action data."""
-    if getattr(log_rerun_data, "blueprint", None) is not None:
-        return
-
-    # Safe + zero-overhead: `log_rerun_data` already ran the `require_package` guard and imported rerun.
-    import rerun as rr
-
-    blueprint = _build_blueprint(observation_paths, action_paths, image_paths)
-    log_rerun_data.blueprint = blueprint
-    rr.send_blueprint(blueprint)
-
-
 def log_rerun_data(
     observation: RobotObservation | None = None,
     action: RobotAction | None = None,
@@ -110,15 +76,11 @@ def log_rerun_data(
     - Scalars values (floats, ints) are logged as `rr.Scalars`.
     - 3D NumPy arrays that resemble images (e.g., with 1, 3, or 4 channels first) are transposed
       from CHW to HWC format, (optionally) compressed to JPEG and logged as `rr.Image` or `rr.EncodedImage`.
-    - 1D NumPy arrays are logged as a single `rr.Scalars` batch under one entity path, so that every
-      dimension shares the same view instead of being split across one view per element.
-    - Multi-dimensional **action** arrays are flattened and logged as a single `rr.Scalars` batch.
+    - 1D NumPy arrays are logged as a series of individual scalars, with each element indexed.
+    - Other multi-dimensional arrays are flattened and logged as individual scalars.
 
     Keys are automatically namespaced with "observation." or "action." if not already present.
 
-    On the first call, a blueprint is built and sent so observation and action scalars get separate
-    time-series views and each image gets its own spatial view.
-
     Args:
         observation: An optional dictionary containing observation data to log.
         action: An optional dictionary containing action data to log.
@@ -128,10 +90,6 @@ def log_rerun_data(
     require_package("rerun-sdk", extra="viz", import_name="rerun")
     import rerun as rr
 
-    observation_paths: set[str] = set()
-    action_paths: set[str] = set()
-    image_paths: set[str] = set()
-
     if observation:
         for k, v in observation.items():
             if v is None:
@@ -140,19 +98,17 @@ def log_rerun_data(
 
             if _is_scalar(v):
                 rr.log(key, rr.Scalars(float(v)))
-                observation_paths.add(key)
             elif isinstance(v, np.ndarray):
                 arr = v
                 # Convert CHW -> HWC when needed
                 if arr.ndim == 3 and arr.shape[0] in (1, 3, 4) and arr.shape[-1] not in (1, 3, 4):
                     arr = np.transpose(arr, (1, 2, 0))
                 if arr.ndim == 1:
-                    rr.log(key, rr.Scalars(arr.astype(float)))
-                    observation_paths.add(key)
+                    for i, vi in enumerate(arr):
+                        rr.log(f"{key}_{i}", rr.Scalars(float(vi)))
                 else:
                     img_entity = rr.Image(arr).compress() if compress_images else rr.Image(arr)
                     rr.log(key, entity=img_entity, static=True)
-                    image_paths.add(key)
 
     if action:
         for k, v in action.items():
@@ -162,9 +118,12 @@ def log_rerun_data(
 
             if _is_scalar(v):
                 rr.log(key, rr.Scalars(float(v)))
-                action_paths.add(key)
             elif isinstance(v, np.ndarray):
-                rr.log(key, rr.Scalars(v.reshape(-1).astype(float)))
-                action_paths.add(key)
-
-    _ensure_blueprint(observation_paths, action_paths, image_paths)
+                if v.ndim == 1:
+                    for i, vi in enumerate(v):
+                        rr.log(f"{key}_{i}", rr.Scalars(float(vi)))
+                else:
+                    # Fall back to flattening higher-dimensional arrays
+                    flat = v.flatten()
+                    for i, vi in enumerate(flat):
+                        rr.log(f"{key}_{i}", rr.Scalars(float(vi)))

tests/datasets/test_sampler.py

@@ -114,6 +114,30 @@ def test_shuffle():
     assert set(sampler) == {0, 1, 2, 3, 4, 5}
 
 
+def test_shuffle_with_generator_is_deterministic():
+    # Two samplers shuffling with same-seed generators must yield identical permutations.
+    # This is what keeps batch shards disjoint across ranks in distributed training, where
+    # accelerate synchronizes the sampler's generator state instead of the global torch RNG.
+    sampler_a = EpisodeAwareSampler([0], [6], shuffle=True, generator=torch.Generator().manual_seed(42))
+    sampler_b = EpisodeAwareSampler([0], [6], shuffle=True, generator=torch.Generator().manual_seed(42))
+    assert list(sampler_a) == list(sampler_b)
+
+    # Desyncing the global RNG must not affect the permutation.
+    sampler_c = EpisodeAwareSampler([0], [6], shuffle=True, generator=torch.Generator().manual_seed(42))
+    order_before = list(sampler_c)
+    sampler_c.generator.manual_seed(42)
+    torch.randperm(1000)  # consume global RNG, as rank-asymmetric code (e.g. eval) would
+    assert list(sampler_c) == order_before
+
+
+def test_generator_attribute_defaults_to_none():
+    # accelerate detects synchronizable samplers via `hasattr(sampler, "generator")`,
+    # so the attribute must exist even when no generator is passed.
+    sampler = EpisodeAwareSampler([0], [6], shuffle=True)
+    assert sampler.generator is None
+    assert set(sampler) == {0, 1, 2, 3, 4, 5}
+
+
 def test_negative_drop_first_frames_raises():
     with pytest.raises(ValueError, match="drop_n_first_frames must be >= 0"):
         EpisodeAwareSampler([0], [10], drop_n_first_frames=-1)

tests/teleoperators/test_rebot_102_leader.py

@@ -18,7 +18,7 @@ from unittest.mock import MagicMock, patch
 
 import pytest
 
-from lerobot.teleoperators.bi_rebot_102_leader import BiRebotArm102Leader, BiRebotArm102LeaderConfig
+from lerobot.teleoperators.bi_rebot_102_leader import BiRebot102Leader, BiRebot102LeaderConfig
 from lerobot.teleoperators.rebot_102_leader import (
     RebotArm102Leader,
     RebotArm102LeaderConfig,
@@ -91,11 +91,11 @@ def test_send_feedback_not_implemented(leader):
 
 def test_bimanual_prefixes_features():
     with patch(f"{_MODULE}.require_package", lambda *a, **kw: None):
-        cfg = BiRebotArm102LeaderConfig(
+        cfg = BiRebot102LeaderConfig(
             left_arm_config=RebotArm102LeaderConfig(port="/dev/null0"),
             right_arm_config=RebotArm102LeaderConfig(port="/dev/null1"),
         )
-        teleop = BiRebotArm102Leader(cfg)
+        teleop = BiRebot102Leader(cfg)
     assert any(k.startswith("left_") for k in teleop.action_features)
     assert any(k.startswith("right_") for k in teleop.action_features)
     assert "left_gripper.pos" in teleop.action_features

tests/utils/test_visualization_utils.py

@@ -30,46 +30,25 @@ from lerobot.utils.constants import OBS_STATE
 @pytest.fixture
 def mock_rerun(monkeypatch):
     """
-    Provide a mock `rerun` module (and `rerun.blueprint` submodule) so tests don't
-    depend on the real library. Also reload the module-under-test so it binds to
-    this mock `rr`.
+    Provide a mock `rerun` module so tests don't depend on the real library.
+    Also reload the module-under-test so it binds to this mock `rr`.
     """
     calls = []
-    blueprints = []
 
     class DummyScalar:
         def __init__(self, value):
-            # Scalars may be built from a single float or from a 1D array batch.
-            self.value = value
+            self.value = float(value)
 
     class DummyImage:
         def __init__(self, arr):
             self.arr = arr
 
-        def compress(self, *a, **k):
-            return self
-
     def dummy_log(key, obj=None, **kwargs):
         # Accept either positional `obj` or keyword `entity` and record remaining kwargs.
         if obj is None and "entity" in kwargs:
             obj = kwargs.pop("entity")
         calls.append((key, obj, kwargs))
 
-    def dummy_send_blueprint(blueprint, *a, **k):
-        blueprints.append(blueprint)
-
-    # Mock the `rerun.blueprint` submodule used to build the layout.
-    dummy_rrb = SimpleNamespace(
-        Spatial2DView=lambda origin=None, name=None: SimpleNamespace(
-            kind="Spatial2DView", origin=origin, name=name
-        ),
-        TimeSeriesView=lambda name=None, contents=None: SimpleNamespace(
-            kind="TimeSeriesView", name=name, contents=contents
-        ),
-        Grid=lambda *views: SimpleNamespace(kind="Grid", views=list(views)),
-        Blueprint=lambda root: SimpleNamespace(kind="Blueprint", root=root),
-    )
-
     dummy_rr = SimpleNamespace(
         __name__="rerun",
         __package__="rerun",
@@ -77,23 +56,20 @@ def mock_rerun(monkeypatch):
         Scalars=DummyScalar,
         Image=DummyImage,
         log=dummy_log,
-        send_blueprint=dummy_send_blueprint,
         init=lambda *a, **k: None,
         spawn=lambda *a, **k: None,
-        blueprint=dummy_rrb,
     )
 
-    # Inject fake modules into sys.modules (both `rerun` and `rerun.blueprint`).
+    # Inject fake module into sys.modules
     monkeypatch.setitem(sys.modules, "rerun", dummy_rr)
-    monkeypatch.setitem(sys.modules, "rerun.blueprint", dummy_rrb)
 
     # Now import and reload the module under test, to bind to our rerun mock
     import lerobot.utils.visualization_utils as vu
 
     importlib.reload(vu)
 
-    # Expose the reloaded module, the call recorder and the captured blueprints
-    yield vu, calls, blueprints
+    # Expose both the reloaded module and the call recorder
+    yield vu, calls
 
 
 def _keys(calls):
@@ -116,13 +92,8 @@ def _kwargs_for(calls, key):
     raise KeyError(f"Key {key} not found in calls: {calls}")
 
 
-def _views_by_kind(blueprint, kind):
-    """Return the views of a given kind from the (single) blueprint's grid."""
-    return [v for v in blueprint.root.views if v.kind == kind]
-
-
 def test_log_rerun_data_envtransition_scalars_and_image(mock_rerun):
-    vu, calls, blueprints = mock_rerun
+    vu, calls = mock_rerun
 
     # Build EnvTransition dict
     obs = {
@@ -132,7 +103,7 @@ def test_log_rerun_data_envtransition_scalars_and_image(mock_rerun):
     }
     act = {
         "action.throttle": 0.7,
-        # 1D array should be logged as a single Scalars batch under one entity path
+        # 1D array should log individual Scalars with suffix _i
         "action.vector": np.array([1.0, 2.0], dtype=np.float32),
     }
     transition = {
@@ -149,28 +120,31 @@ def test_log_rerun_data_envtransition_scalars_and_image(mock_rerun):
     # - observation.state.temperature -> Scalars
     # - observation.camera -> Image (HWC) with static=True
     # - action.throttle -> Scalars
-    # - action.vector -> single Scalars batch (no per-element suffix)
+    # - action.vector_0, action.vector_1 -> Scalars
     expected_keys = {
         f"{OBS_STATE}.temperature",
         "observation.camera",
         "action.throttle",
-        "action.vector",
+        "action.vector_0",
+        "action.vector_1",
     }
     assert set(_keys(calls)) == expected_keys
 
     # Check scalar types and values
     temp_obj = _obj_for(calls, f"{OBS_STATE}.temperature")
     assert type(temp_obj).__name__ == "DummyScalar"
-    assert float(temp_obj.value) == pytest.approx(25.0)
+    assert temp_obj.value == pytest.approx(25.0)
 
     throttle_obj = _obj_for(calls, "action.throttle")
     assert type(throttle_obj).__name__ == "DummyScalar"
-    assert float(throttle_obj.value) == pytest.approx(0.7)
+    assert throttle_obj.value == pytest.approx(0.7)
 
-    # 1D vector logged as a single batched Scalars under one entity path
-    vec = _obj_for(calls, "action.vector")
-    assert type(vec).__name__ == "DummyScalar"
-    np.testing.assert_allclose(np.asarray(vec.value), [1.0, 2.0])
+    v0 = _obj_for(calls, "action.vector_0")
+    v1 = _obj_for(calls, "action.vector_1")
+    assert type(v0).__name__ == "DummyScalar"
+    assert type(v1).__name__ == "DummyScalar"
+    assert v0.value == pytest.approx(1.0)
+    assert v1.value == pytest.approx(2.0)
 
     # Check image handling: CHW -> HWC
     img_obj = _obj_for(calls, "observation.camera")
@@ -178,24 +152,9 @@ def test_log_rerun_data_envtransition_scalars_and_image(mock_rerun):
     assert img_obj.arr.shape == (10, 20, 3)  # transposed
     assert _kwargs_for(calls, "observation.camera").get("static", False) is True  # static=True for images
 
-    # A blueprint should have been built and sent exactly once, and cached on the function.
-    assert len(blueprints) == 1
-    assert vu.log_rerun_data.blueprint is blueprints[0]
-
-    bp = blueprints[0]
-    # One spatial view per image path
-    spatial_views = _views_by_kind(bp, "Spatial2DView")
-    assert {v.origin for v in spatial_views} == {"observation.camera"}
-
-    # One time-series view each for observation and action scalars
-    ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
-    assert set(ts_views) == {"observation", "action"}
-    assert ts_views["observation"].contents == [f"{OBS_STATE}.temperature"]
-    assert ts_views["action"].contents == ["action.throttle", "action.vector"]
-
 
 def test_log_rerun_data_plain_list_ordering_and_prefixes(mock_rerun):
-    vu, calls, blueprints = mock_rerun
+    vu, calls = mock_rerun
 
     # First dict without prefixes treated as observation
     # Second dict without prefixes treated as action
@@ -214,12 +173,14 @@ def test_log_rerun_data_plain_list_ordering_and_prefixes(mock_rerun):
     # First dict was treated as observation, second as action
     vu.log_rerun_data(observation=obs_plain, action=act_plain)
 
-    # Expected keys with auto-prefixes. The 1D vector is a single batched Scalars.
+    # Expected keys with auto-prefixes
     expected = {
         "observation.temp",
         "observation.img",
         "action.throttle",
-        "action.vec",
+        "action.vec_0",
+        "action.vec_1",
+        "action.vec_2",
     }
     logged = set(_keys(calls))
     assert logged == expected
@@ -227,11 +188,11 @@ def test_log_rerun_data_plain_list_ordering_and_prefixes(mock_rerun):
     # Scalars
     t = _obj_for(calls, "observation.temp")
     assert type(t).__name__ == "DummyScalar"
-    assert float(t.value) == pytest.approx(1.5)
+    assert t.value == pytest.approx(1.5)
 
     throttle = _obj_for(calls, "action.throttle")
     assert type(throttle).__name__ == "DummyScalar"
-    assert float(throttle.value) == pytest.approx(0.3)
+    assert throttle.value == pytest.approx(0.3)
 
     # Image stays HWC
     img = _obj_for(calls, "observation.img")
@@ -239,23 +200,15 @@ def test_log_rerun_data_plain_list_ordering_and_prefixes(mock_rerun):
     assert img.arr.shape == (5, 6, 3)
     assert _kwargs_for(calls, "observation.img").get("static", False) is True
 
-    # Vector logged as a single batched Scalars under one entity path
-    vec = _obj_for(calls, "action.vec")
-    assert type(vec).__name__ == "DummyScalar"
-    np.testing.assert_allclose(np.asarray(vec.value), [9, 8, 7])
-
-    # Blueprint sent once with the expected view layout
-    assert len(blueprints) == 1
-    bp = blueprints[0]
-    spatial_views = _views_by_kind(bp, "Spatial2DView")
-    assert {v.origin for v in spatial_views} == {"observation.img"}
-    ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
-    assert ts_views["observation"].contents == ["observation.temp"]
-    assert ts_views["action"].contents == ["action.throttle", "action.vec"]
+    # Vectors
+    for i, val in enumerate([9, 8, 7]):
+        o = _obj_for(calls, f"action.vec_{i}")
+        assert type(o).__name__ == "DummyScalar"
+        assert o.value == pytest.approx(val)
 
 
 def test_log_rerun_data_kwargs_only(mock_rerun):
-    vu, calls, blueprints = mock_rerun
+    vu, calls = mock_rerun
 
     vu.log_rerun_data(
         observation={"observation.temp": 10.0, "observation.gray": np.zeros((8, 8, 1), dtype=np.uint8)},
@@ -269,7 +222,7 @@ def test_log_rerun_data_kwargs_only(mock_rerun):
 
     temp = _obj_for(calls, "observation.temp")
     assert type(temp).__name__ == "DummyScalar"
-    assert float(temp.value) == pytest.approx(10.0)
+    assert temp.value == pytest.approx(10.0)
 
     img = _obj_for(calls, "observation.gray")
     assert type(img).__name__ == "DummyImage"
@@ -278,26 +231,4 @@ def test_log_rerun_data_kwargs_only(mock_rerun):
 
     a = _obj_for(calls, "action.a")
     assert type(a).__name__ == "DummyScalar"
-    assert float(a.value) == pytest.approx(1.0)
-
-    # Blueprint sent once, with a spatial view for the image and time-series views for scalars
-    assert len(blueprints) == 1
-    bp = blueprints[0]
-    assert {v.origin for v in _views_by_kind(bp, "Spatial2DView")} == {"observation.gray"}
-    ts_views = {v.name: v for v in _views_by_kind(bp, "TimeSeriesView")}
-    assert ts_views["observation"].contents == ["observation.temp"]
-    assert ts_views["action"].contents == ["action.a"]
-
-
-def test_log_rerun_data_blueprint_sent_only_once(mock_rerun):
-    """The blueprint is built from the first call and not resent on subsequent calls."""
-    vu, calls, blueprints = mock_rerun
-
-    vu.log_rerun_data(observation={"temp": 1.0}, action={"a": 2.0})
-    assert len(blueprints) == 1
-    first_blueprint = vu.log_rerun_data.blueprint
-
-    vu.log_rerun_data(observation={"temp": 3.0}, action={"a": 4.0})
-    # Still only one blueprint, and the cached one is unchanged.
-    assert len(blueprints) == 1
-    assert vu.log_rerun_data.blueprint is first_blueprint
+    assert a.value == pytest.approx(1.0)

uv.lock

@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.12"
 resolution-markers = [
     "(python_full_version >= '3.15' and platform_machine == 'AMD64' and sys_platform == 'linux') or (python_full_version >= '3.15' and platform_machine == 'x86_64' and sys_platform == 'linux')",
@@ -3257,7 +3257,7 @@ requires-dist = [
     { name = "qwen-vl-utils", marker = "extra == 'qwen-vl-utils-dep'", specifier = ">=0.0.11,<0.1.0" },
     { name = "reachy2-sdk", marker = "extra == 'reachy2'", specifier = ">=1.0.15,<1.1.0" },
     { name = "requests", specifier = ">=2.32.0,<3.0.0" },
-    { name = "rerun-sdk", marker = "extra == 'viz'", specifier = ">=0.24.0,<0.34.0" },
+    { name = "rerun-sdk", marker = "extra == 'viz'", specifier = ">=0.24.0,<0.27.0" },
     { name = "ruff", marker = "extra == 'dev'", specifier = ">=0.14.1" },
     { name = "safetensors", specifier = ">=0.4.3,<1.0.0" },
     { name = "scikit-image", marker = "extra == 'video-benchmark'", specifier = ">=0.23.2,<0.26.0" },
@@ -5636,21 +5636,21 @@ wheels = [
 
 [[package]]
 name = "rerun-sdk"
-version = "0.33.0"
+version = "0.26.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "attrs" },
     { name = "numpy" },
     { name = "pillow" },
-    { name = "psutil" },
     { name = "pyarrow" },
     { name = "typing-extensions" },
 ]
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/31/17/5a521e86ac0064bd0f452e3e98e2422433511b54110423c0217d2cc1234f/rerun_sdk-0.33.0-cp310-abi3-macosx_11_0_arm64.whl", hash = "sha256:97f123e3ef6aa69b60194bc566e5435c7d4040757ed4f58297ea46c8ef320c5c", size = 125707606, upload-time = "2026-05-29T09:42:53.584Z" },
-    { url = "https://files.pythonhosted.org/packages/34/2f/2ca2599aca03b69fbcac7c8391ef50376968edd7c58b96de53a4b7f20624/rerun_sdk-0.33.0-cp310-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:8f734cf59419dcfbc46915bea6cec030224f16e96c3a597f0ccf7cb7b058dd43", size = 135271020, upload-time = "2026-05-29T09:43:00.106Z" },
-    { url = "https://files.pythonhosted.org/packages/2e/ba/d70997b43e6db4f58c4326c29c6a6a384ddc6c2fe125f231c885ad9b3b1f/rerun_sdk-0.33.0-cp310-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:53d95609f8b330026bcd041bf6d11b46ee1c18b6fbde155135f291fe86328eeb", size = 139552018, upload-time = "2026-05-29T09:43:06.275Z" },
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