filesize default change + more logs + filesize mb based episode + go back to init pos + rerun log + date end of repo_id

src/lerobot/configs/dataset.py

@@ -15,6 +15,7 @@
 """Shared dataset recording configuration used by both ``lerobot-record`` and ``lerobot-rollout``."""
 
 from dataclasses import dataclass, field
+from datetime import datetime
 from pathlib import Path
 
 
@@ -69,3 +70,8 @@ class DatasetRecordConfig:
     encoder_threads: int | None = None
     # Rename map for the observation to override the image and state keys
     rename_map: dict[str, str] = field(default_factory=dict)
+
+    def __post_init__(self) -> None:
+        if self.repo_id:
+            timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+            self.repo_id = f"{self.repo_id}_{timestamp}"

src/lerobot/datasets/utils.py

@@ -71,8 +71,8 @@ class ForwardCompatibilityError(CompatibilityError):
 
 
 DEFAULT_CHUNK_SIZE = 1000  # Max number of files per chunk
-DEFAULT_DATA_FILE_SIZE_IN_MB = 100  # Max size per file
+DEFAULT_DATA_FILE_SIZE_IN_MB = 50  # Max size per file
-DEFAULT_VIDEO_FILE_SIZE_IN_MB = 200  # Max size per file
+DEFAULT_VIDEO_FILE_SIZE_IN_MB = 100  # Max size per file
 
 INFO_PATH = "meta/info.json"
 STATS_PATH = "meta/stats.json"

src/lerobot/rollout/configs.py

@@ -62,12 +62,19 @@ class BaseStrategyConfig(RolloutStrategyConfig):
 class SentryStrategyConfig(RolloutStrategyConfig):
     """Continuous autonomous rollout with always-on recording.
 
-    Episodes are auto-rotated every ``episode_duration_s`` seconds and
+    Episode duration is derived from camera resolution, FPS, and
-    uploaded in the background every ``upload_every_n_episodes`` episodes.
+    ``target_video_file_size_mb`` so that each saved episode produces a
+    video file that has crossed the target size.  This aligns episode
+    boundaries with the dataset's video file chunking, so each
+    ``push_to_hub`` call uploads complete video files rather than
+    re-uploading a growing file that hasn't crossed the chunk boundary.
     """
 
-    episode_duration_s: float = 20.0
     upload_every_n_episodes: int = 5
+    # Target video file size in MB for episode rotation.  Episodes are
+    # saved once the estimated video duration would exceed this limit.
+    # Defaults to DEFAULT_VIDEO_FILE_SIZE_IN_MB when set to None.
+    target_video_file_size_mb: float | None = None
 
 
 @RolloutStrategyConfig.register_subclass("highlight")
@@ -129,15 +136,18 @@ class DAggerStrategyConfig(RolloutStrategyConfig):
     3. **upload** — push dataset to hub on demand (corrections-only mode).
 
     When ``record_autonomous=True`` (default) both autonomous and correction
-    frames are recorded with sentry-like time-based episode rotation and
+    frames are recorded with size-based episode rotation (same as Sentry)
-    background uploading.  Set to ``False`` to record only the human-correction
+    and background uploading.  ``push_to_hub`` is blocked while a correction
+    is in progress.  Set to ``False`` to record only the human-correction
     windows, where each correction becomes its own episode.
     """
 
-    episode_time_s: float = 20.0
     num_episodes: int = 10
     record_autonomous: bool = False
     upload_every_n_episodes: int = 5
+    # Target video file size in MB for episode rotation (record_autonomous
+    # mode only).  Defaults to DEFAULT_VIDEO_FILE_SIZE_IN_MB when None.
+    target_video_file_size_mb: float | None = None
     input_device: str = "keyboard"
     keyboard: DAggerKeyboardConfig = field(default_factory=DAggerKeyboardConfig)
     pedal: DAggerPedalConfig = field(default_factory=DAggerPedalConfig)
@@ -184,6 +194,14 @@ class RolloutConfig:
     device: str | None = None
     task: str = ""
     display_data: bool = False
+    # Display data on a remote Rerun server
+    display_ip: str | None = None
+    # Port of the remote Rerun server
+    display_port: int | None = None
+    # Whether to display compressed images in Rerun
+    display_compressed_images: bool = False
+    # Use vocal synthesis to read events
+    play_sounds: bool = True
     resume: bool = False
 
     # Torch compile

src/lerobot/rollout/context.py

@@ -98,10 +98,15 @@ class HardwareContext:
     The raw robot is available via ``robot_wrapper.inner`` when needed
     (e.g. for disconnect); strategies should otherwise go through the
     thread-safe wrapper.
+
+    ``initial_position`` stores the robot's joint positions at connect
+    time.  Strategies use it to return the robot to a safe pose before
+    shutting down.
     """
 
     robot_wrapper: ThreadSafeRobot
     teleop: Teleoperator | None
+    initial_position: dict | None = None
 
 
 @dataclass
@@ -167,6 +172,7 @@ def build_rollout_context(
     is_rtc = isinstance(cfg.inference, RTCInferenceConfig)
 
     # --- 1. Policy (heavy I/O, but no hardware yet) -------------------
+    logger.info("Loading policy from '%s'...", cfg.policy.pretrained_path)
     policy_config = cfg.policy
     policy_class = get_policy_class(policy_config.type)
 
@@ -199,6 +205,7 @@ def build_rollout_context(
 
     policy = policy.to(cfg.device)
     policy.eval()
+    logger.info("Policy loaded: type=%s, device=%s", policy_config.type, cfg.device)
 
     if cfg.use_torch_compile and policy.type not in ("pi0", "pi05"):
         try:
@@ -225,14 +232,24 @@ def build_rollout_context(
         robot_observation_processor = robot_observation_processor or _o
 
     # --- 3. Hardware (heaviest side-effect, deferred) -----------------
+    logger.info("Connecting robot (%s)...", cfg.robot.type if cfg.robot else "?")
     robot = make_robot_from_config(cfg.robot)
     robot.connect()
+    logger.info("Robot connected: %s", robot.name)
+
+    # Store the initial joint positions so we can return to a safe pose on shutdown.
+    initial_obs = robot.get_observation()
+    initial_position = {k: v for k, v in initial_obs.items() if k.endswith(".pos")}
+    logger.info("Captured initial robot position (%d keys)", len(initial_position))
+
     robot_wrapper = ThreadSafeRobot(robot)
 
     teleop = None
     if cfg.teleop is not None:
+        logger.info("Connecting teleoperator (%s)...", cfg.teleop.type if cfg.teleop else "?")
         teleop = make_teleoperator_from_config(cfg.teleop)
         teleop.connect()
+        logger.info("Teleoperator connected")
 
     # DAgger requires teleop with motor control capabilities (enable_torque,
     # disable_torque, write_goal_positions).
@@ -280,6 +297,7 @@ def build_rollout_context(
     # --- 5. Dataset -------------
     dataset = None
     if cfg.dataset is not None and not isinstance(cfg.strategy, BaseStrategyConfig):
+        logger.info("Setting up dataset (repo_id=%s)...", cfg.dataset.repo_id)
         if cfg.resume:
             dataset = LeRobotDataset.resume(
                 cfg.dataset.repo_id,
@@ -318,6 +336,9 @@ def build_rollout_context(
                 encoder_threads=cfg.dataset.encoder_threads,
             )
 
+    if dataset is not None:
+        logger.info("Dataset ready: %s (%d existing episodes)", dataset.repo_id, dataset.num_episodes)
+
     # --- 6. Policy pre/post processors (needs dataset stats if any) ---
     dataset_stats = None
     if dataset is not None:
@@ -337,6 +358,10 @@ def build_rollout_context(
     )
 
     # --- 7. Inference strategy (needs policy + pre/post + hardware) --
+    logger.info(
+        "Creating inference engine (type=%s)...",
+        cfg.inference.type if hasattr(cfg.inference, "type") else "sync",
+    )
     task_str = cfg.dataset.single_task if cfg.dataset else cfg.task
     inference_strategy = create_inference_engine(
         cfg.inference,
@@ -356,9 +381,12 @@ def build_rollout_context(
     )
 
     # --- 8. Assemble ---------------------------------------------------
+    logger.info("Rollout context assembled successfully")
     return RolloutContext(
         runtime=RuntimeContext(cfg=cfg, shutdown_event=shutdown_event),
-        hardware=HardwareContext(robot_wrapper=robot_wrapper, teleop=teleop),
+        hardware=HardwareContext(
+            robot_wrapper=robot_wrapper, teleop=teleop, initial_position=initial_position
+        ),
         policy=PolicyContext(
             policy=policy,
             preprocessor=preprocessor,

src/lerobot/rollout/inference/factory.py

@@ -98,6 +98,7 @@ def create_inference_engine(
     shutdown_event: Event | None = None,
 ) -> InferenceEngine:
     """Instantiate the appropriate inference engine from a config object."""
+    logger.info("Creating inference engine: %s", config.type)
     if isinstance(config, SyncInferenceConfig):
         return SyncInferenceEngine(
             policy=policy,

src/lerobot/rollout/inference/rtc.py

@@ -158,6 +158,12 @@ class RTCInferenceEngine(InferenceEngine):
 
         if not self._use_torch_compile:
             self._compile_warmup_done.set()
+            logger.info("RTCInferenceEngine initialized (torch.compile disabled, no warmup needed)")
+        else:
+            logger.info(
+                "RTCInferenceEngine initialized (torch.compile enabled, %d warmup inferences)",
+                compile_warmup_inferences,
+            )
 
         # Processor introspection for relative-action re-anchoring.
         self._relative_step = next(
@@ -216,22 +222,30 @@ class RTCInferenceEngine(InferenceEngine):
 
     def stop(self) -> None:
         """Signal the RTC thread to stop and wait for it."""
+        logger.info("Stopping RTC inference thread...")
         self._shutdown_event.set()
         self._policy_active.clear()
         if self._rtc_thread is not None and self._rtc_thread.is_alive():
             self._rtc_thread.join(timeout=_RTC_JOIN_TIMEOUT_S)
+            if self._rtc_thread.is_alive():
+                logger.warning("RTC thread did not join within %.1fs", _RTC_JOIN_TIMEOUT_S)
+            else:
+                logger.info("RTC inference thread stopped")
             self._rtc_thread = None
 
     def pause(self) -> None:
         """Pause the RTC background thread."""
+        logger.info("Pausing RTC inference thread")
         self._policy_active.clear()
 
     def resume(self) -> None:
         """Resume the RTC background thread."""
+        logger.info("Resuming RTC inference thread")
         self._policy_active.set()
 
     def reset(self) -> None:
         """Reset the policy, processors, and action queue."""
+        logger.info("Resetting RTC inference state (policy + processors + queue)")
         self._policy.reset()
         self._preprocessor.reset()
         self._postprocessor.reset()

src/lerobot/rollout/inference/sync.py

@@ -58,15 +58,23 @@ class SyncInferenceEngine(InferenceEngine):
         self._task = task
         self._device = torch.device(device or "cpu")
         self._robot_type = robot_type
+        logger.info(
+            "SyncInferenceEngine initialized (device=%s, action_keys=%d)",
+            self._device,
+            len(ordered_action_keys),
+        )
 
     def start(self) -> None:
         """No background resources to start."""
+        logger.info("SyncInferenceEngine started (inline mode — no background thread)")
 
     def stop(self) -> None:
         """No background resources to stop."""
+        logger.info("SyncInferenceEngine stopped")
 
     def reset(self) -> None:
         """Reset the policy and pre/post-processors."""
+        logger.info("Resetting sync inference state (policy + processors)")
         self._policy.reset()
         self._preprocessor.reset()
         self._postprocessor.reset()

src/lerobot/rollout/strategies/__init__.py

@@ -14,11 +14,13 @@
 
 """Rollout strategies — public API re-exports."""
 
-from .core import RolloutStrategy, send_next_action
+from .core import RolloutStrategy, estimate_max_episode_seconds, safe_push_to_hub, send_next_action
 from .factory import create_strategy
 
 __all__ = [
     "RolloutStrategy",
     "create_strategy",
+    "estimate_max_episode_seconds",
+    "safe_push_to_hub",
     "send_next_action",
 ]

src/lerobot/rollout/strategies/base.py

@@ -50,11 +50,13 @@ class BaseStrategy(RolloutStrategy):
 
         start_time = time.perf_counter()
         engine.resume()
+        logger.info("Base strategy control loop started")
 
         while not ctx.runtime.shutdown_event.is_set():
             loop_start = time.perf_counter()
 
             if cfg.duration > 0 and (time.perf_counter() - start_time) >= cfg.duration:
+                logger.info("Duration limit reached (%.0fs)", cfg.duration)
                 break
 
             obs = robot.get_observation()
@@ -64,7 +66,8 @@ class BaseStrategy(RolloutStrategy):
             if self._handle_warmup(cfg.use_torch_compile, loop_start, control_interval):
                 continue
 
-            send_next_action(obs_processed, obs, ctx, interpolator)
+            action_dict = send_next_action(obs_processed, obs, ctx, interpolator)
+            self._log_telemetry(obs_processed, action_dict, ctx.runtime)
 
             dt = time.perf_counter() - loop_start
             if (sleep_t := control_interval - dt) > 0:

src/lerobot/rollout/strategies/core.py

@@ -17,19 +17,24 @@
 from __future__ import annotations
 
 import abc
+import logging
 import time
 from typing import TYPE_CHECKING
 
+from lerobot.datasets.utils import DEFAULT_VIDEO_FILE_SIZE_IN_MB
 from lerobot.utils.action_interpolator import ActionInterpolator
 from lerobot.utils.constants import OBS_STR
 from lerobot.utils.feature_utils import build_dataset_frame
 from lerobot.utils.robot_utils import precise_sleep
+from lerobot.utils.visualization_utils import log_rerun_data
 
 from ..inference import InferenceEngine
 
 if TYPE_CHECKING:
     from ..configs import RolloutStrategyConfig
-    from ..context import HardwareContext, RolloutContext
+    from ..context import HardwareContext, RolloutContext, RuntimeContext
+
+logger = logging.getLogger(__name__)
 
 
 class RolloutStrategy(abc.ABC):
@@ -54,8 +59,10 @@ class RolloutStrategy(abc.ABC):
         """
         self._interpolator = ActionInterpolator(multiplier=ctx.runtime.cfg.interpolation_multiplier)
         self._engine = ctx.policy.inference
+        logger.info("Starting inference engine...")
         self._engine.start()
         self._warmup_flushed = False
+        logger.info("Inference engine started")
 
     def _handle_warmup(self, use_torch_compile: bool, loop_start: float, control_interval: float) -> bool:
         """Handle torch.compile warmup phase.
@@ -74,6 +81,7 @@ class RolloutStrategy(abc.ABC):
                 precise_sleep(sleep_t)
             return True
         if not self._warmup_flushed:
+            logger.info("Warmup complete — flushing stale state and resuming engine")
             engine.reset()
             interpolator.reset()
             self._warmup_flushed = True
@@ -81,16 +89,57 @@ class RolloutStrategy(abc.ABC):
         return False
 
     def _teardown_hardware(self, hw: HardwareContext) -> None:
-        """Stop the inference engine and disconnect hardware."""
+        """Stop the inference engine, return robot to initial position, and disconnect hardware."""
         if self._engine is not None:
+            logger.info("Stopping inference engine...")
             self._engine.stop()
         robot = hw.robot_wrapper.inner
         if robot.is_connected:
+            if hw.initial_position:
+                logger.info("Returning robot to initial position before shutdown...")
+                self._return_to_initial_position(hw)
+            logger.info("Disconnecting robot...")
             robot.disconnect()
         teleop = hw.teleop
         if teleop is not None and teleop.is_connected:
+            logger.info("Disconnecting teleoperator...")
             teleop.disconnect()
 
+    @staticmethod
+    def _return_to_initial_position(hw: HardwareContext, duration_s: float = 3.0, fps: int = 50) -> None:
+        """Smoothly interpolate the robot back to its initial position."""
+        robot = hw.robot_wrapper
+        target = hw.initial_position
+        try:
+            current_obs = robot.get_observation()
+            current_pos = {k: v for k, v in current_obs.items() if k in target}
+            steps = max(int(duration_s * fps), 1)
+            for step in range(1, steps + 1):
+                t = step / steps
+                interp = {}
+                for k in current_pos:
+                    interp[k] = current_pos[k] * (1 - t) + target[k] * t
+                robot.send_action(interp)
+                precise_sleep(1 / fps)
+        except Exception as e:
+            logger.warning("Could not return to initial position: %s", e)
+
+    @staticmethod
+    def _log_telemetry(
+        obs_processed: dict | None,
+        action_dict: dict | None,
+        runtime_ctx: RuntimeContext,
+    ) -> None:
+        """Log observation/action telemetry to Rerun if display_data is enabled."""
+        cfg = runtime_ctx.cfg
+        if not cfg.display_data:
+            return
+        log_rerun_data(
+            observation=obs_processed,
+            action=action_dict,
+            compress_images=cfg.display_compressed_images,
+        )
+
     @abc.abstractmethod
     def setup(self, ctx: RolloutContext) -> None:
         """Strategy-specific initialisation (keyboard listeners, buffers, etc.)."""
@@ -104,6 +153,82 @@ class RolloutStrategy(abc.ABC):
         """Cleanup: save dataset, stop threads, disconnect hardware."""
 
 
+# ---------------------------------------------------------------------------
+# Shared helpers
+# ---------------------------------------------------------------------------
+
+
+def safe_push_to_hub(dataset, tags=None, private=False) -> bool:
+    """Push dataset to hub, skipping if no episodes have been saved.
+
+    Returns ``True`` if the push was attempted, ``False`` if skipped.
+    """
+    if dataset.num_episodes == 0:
+        logger.warning("No episodes saved — skipping push to hub")
+        return False
+    dataset.push_to_hub(tags=tags, private=private)
+    return True
+
+
+def estimate_max_episode_seconds(
+    dataset_features: dict,
+    fps: float,
+    target_size_mb: float = DEFAULT_VIDEO_FILE_SIZE_IN_MB,
+) -> float:
+    """Conservatively estimate how many seconds of video will exceed *target_size_mb*.
+
+    Each camera produces its own video file, so the episode duration is
+    driven by the **slowest** camera to fill ``target_size_mb`` — i.e.
+    the one with the fewest pixels per frame (lowest bitrate).
+
+    Uses a deliberately **low** bits-per-pixel estimate so the computed
+    duration is *longer* than reality.  By the time the timer fires the
+    actual video file is guaranteed to have crossed the target size,
+    which aligns episode boundaries with the dataset's video-file
+    chunking — each ``push_to_hub`` uploads complete files rather than
+    re-uploading a still-growing one.
+
+    The estimate ignores codec-specific settings (CRF, preset) on purpose:
+    we only need a rough lower bound on bitrate, not a precise prediction.
+
+    Falls back to 600 s (10 min) when no video features are present.
+    """
+    # 0.1 bits-per-pixel is a *low* estimate for CRF-30 streaming video of
+    # robot footage (real-world is typically 0.1 – 0.3 bpp).  Under-
+    # estimating the bitrate over-estimates the time → the episode will be
+    # *larger* than target_size_mb when we save, which is what we want.
+    conservative_bpp = 0.1
+
+    # Collect per-camera pixel counts — each camera has its own video file.
+    camera_pixels = []
+    for feat in dataset_features.values():
+        if feat.get("dtype") == "video":
+            shape = feat.get("shape", ())
+
+            # Assuming shape could be (C, H, W) or (T, C, H, W)
+            # We want to extract the spatial dimensions.
+            if len(shape) >= 3:
+                h, w = shape[-2], shape[-1]
+                pixels = h * w
+                if pixels > 0:
+                    camera_pixels.append(pixels)
+
+    if not camera_pixels:
+        return 600.0
+
+    # Use the smallest camera: it produces the lowest bitrate and therefore
+    # takes the longest to reach the target — the conservative choice.
+    min_pixels = min(camera_pixels)
+    bits_per_frame = min_pixels * conservative_bpp
+    bytes_per_second = (bits_per_frame * fps) / 8
+
+    # Guard against division by zero just in case
+    if bytes_per_second <= 0:
+        return 600.0
+
+    return (target_size_mb * 1024 * 1024) / bytes_per_second
+
+
 # ---------------------------------------------------------------------------
 # Shared action-dispatch helper
 # ---------------------------------------------------------------------------

src/lerobot/rollout/strategies/dagger.py

@@ -50,17 +50,19 @@ import numpy as np
 
 from lerobot.common.control_utils import is_headless
 from lerobot.datasets import VideoEncodingManager
+from lerobot.datasets.utils import DEFAULT_VIDEO_FILE_SIZE_IN_MB
 from lerobot.teleoperators import Teleoperator
 from lerobot.utils.constants import ACTION, OBS_STR
 from lerobot.utils.feature_utils import build_dataset_frame
 from lerobot.utils.import_utils import _pynput_available
 from lerobot.utils.pedal import start_pedal_listener
 from lerobot.utils.robot_utils import precise_sleep
+from lerobot.utils.utils import log_say
 
 from ..configs import DAggerKeyboardConfig, DAggerPedalConfig, DAggerStrategyConfig
 from ..context import RolloutContext
 from ..robot_wrapper import ThreadSafeRobot
-from .core import RolloutStrategy, send_next_action
+from .core import RolloutStrategy, estimate_max_episode_seconds, safe_push_to_hub, send_next_action
 
 PYNPUT_AVAILABLE = _pynput_available
 keyboard = None
@@ -249,6 +251,12 @@ def _init_dagger_keyboard(events: DAggerEvents, cfg: DAggerKeyboardConfig):
 
     listener = keyboard.Listener(on_press=on_press)
     listener.start()
+    logger.info(
+        "DAgger keyboard listener started (pause_resume='%s', correction='%s', upload='%s', ESC=stop)",
+        cfg.pause_resume,
+        cfg.correction,
+        cfg.upload,
+    )
     return listener
 
 
@@ -268,6 +276,7 @@ def _init_dagger_pedal(events: DAggerEvents, cfg: DAggerPedalConfig):
         if code == cfg.upload:
             events.upload_requested.set()
 
+    logger.info("Initializing DAgger foot pedal listener (device=%s)", cfg.device_path)
     return start_pedal_listener(on_press, device_path=cfg.device_path)
 
 
@@ -307,6 +316,10 @@ class DAggerStrategy(RolloutStrategy):
         """Initialise the inference engine and input device listener."""
         self._init_engine(ctx)
         self._push_executor = ThreadPoolExecutor(max_workers=1, thread_name_prefix="dagger-push")
+        target_mb = self.config.target_video_file_size_mb or DEFAULT_VIDEO_FILE_SIZE_IN_MB
+        self._episode_duration_s = estimate_max_episode_seconds(
+            ctx.data.dataset_features, ctx.runtime.cfg.fps, target_size_mb=target_mb
+        )
 
         if self.config.input_device == "keyboard":
             self._listener = _init_dagger_keyboard(self._events, self.config.keyboard)
@@ -315,10 +328,11 @@ class DAggerStrategy(RolloutStrategy):
 
         record_mode = "all frames (sentry-like)" if self.config.record_autonomous else "corrections only"
         logger.info(
-            "DAgger strategy ready (input=%s, episodes=%d, record=%s)",
+            "DAgger strategy ready (input=%s, episodes=%d, record=%s, episode_duration=%.0fs)",
             self.config.input_device,
             self.config.num_episodes,
             record_mode,
+            self._episode_duration_s,
         )
 
     def run(self, ctx: RolloutContext) -> None:
@@ -330,21 +344,32 @@ class DAggerStrategy(RolloutStrategy):
 
     def teardown(self, ctx: RolloutContext) -> None:
         """Stop listeners, finalise the dataset, and disconnect hardware."""
+        play_sounds = ctx.runtime.cfg.play_sounds
+        logger.info("Stopping DAgger recording")
+        log_say("Stopping DAgger recording", play_sounds)
+
         if self._listener is not None and not is_headless():
+            logger.info("Stopping keyboard listener")
             self._listener.stop()
 
         # Flush any queued/running push cleanly
         if self._push_executor is not None:
+            logger.info("Shutting down push executor (waiting for pending pushes)...")
             self._push_executor.shutdown(wait=True)
             self._push_executor = None
 
         if ctx.data.dataset is not None:
+            logger.info("Finalizing dataset...")
             ctx.data.dataset.finalize()
             if self._needs_push.is_set() and ctx.runtime.cfg.dataset and ctx.runtime.cfg.dataset.push_to_hub:
-                ctx.data.dataset.push_to_hub(
+                logger.info("Pushing final dataset to hub...")
+                if safe_push_to_hub(
+                    ctx.data.dataset,
                     tags=ctx.runtime.cfg.dataset.tags,
                     private=ctx.runtime.cfg.dataset.private,
-                )
+                ):
+                    logger.info("Dataset uploaded to hub")
+                    log_say("Dataset uploaded to hub", play_sounds)
 
         self._teardown_hardware(ctx.hardware)
         logger.info("DAgger strategy teardown complete")
@@ -373,6 +398,7 @@ class DAggerStrategy(RolloutStrategy):
         control_interval = interpolator.get_control_interval(cfg.fps)
         record_stride = max(1, cfg.interpolation_multiplier)
         task_str = cfg.dataset.single_task if cfg.dataset else cfg.task
+        play_sounds = cfg.play_sounds
 
         engine.reset()
         interpolator.reset()
@@ -384,9 +410,11 @@ class DAggerStrategy(RolloutStrategy):
 
         last_action: dict[str, Any] | None = None
         record_tick = 0
-        episode_start = time.perf_counter()
         start_time = time.perf_counter()
+        episode_start = time.perf_counter()
         episodes_since_push = 0
+        episode_duration_s = self._episode_duration_s
+        logger.info("DAgger continuous recording started (episode_duration=%.0fs)", episode_duration_s)
 
         with VideoEncodingManager(dataset):
             try:
@@ -394,6 +422,7 @@ class DAggerStrategy(RolloutStrategy):
                     loop_start = time.perf_counter()
 
                     if cfg.duration > 0 and (time.perf_counter() - start_time) >= cfg.duration:
+                        logger.info("Duration limit reached (%.0fs)", cfg.duration)
                         break
 
                     # Process transitions
@@ -415,6 +444,7 @@ class DAggerStrategy(RolloutStrategy):
                         robot_action_to_send = ctx.processors.robot_action_processor((processed_teleop, obs))
                         robot.send_action(robot_action_to_send)
                         last_action = robot_action_to_send
+                        self._log_telemetry(obs_processed, processed_teleop, ctx.runtime)
                         action_frame = build_dataset_frame(features, processed_teleop, prefix=ACTION)
                         if record_tick % record_stride == 0:
                             frame = {
@@ -440,6 +470,7 @@ class DAggerStrategy(RolloutStrategy):
 
                         action_dict = send_next_action(obs_processed, obs, ctx, interpolator)
                         if action_dict is not None:
+                            self._log_telemetry(obs_processed, action_dict, ctx.runtime)
                             last_action = ctx.processors.robot_action_processor((action_dict, obs))
                             action_frame = build_dataset_frame(features, action_dict, prefix=ACTION)
                             if record_tick % record_stride == 0:
@@ -452,14 +483,21 @@ class DAggerStrategy(RolloutStrategy):
                                 dataset.add_frame(frame)
                             record_tick += 1
 
-                    # Sentry-like episode rotation
+                    # Episode rotation derived from video file-size target.
+                    # Do NOT save mid-correction — wait for the correction
+                    # to finish so the episode boundary is clean.
                     elapsed = time.perf_counter() - episode_start
-                    if elapsed >= self.config.episode_time_s:
+                    if elapsed >= episode_duration_s and phase != DAggerPhase.CORRECTING:
                         with self._episode_lock:
                             dataset.save_episode()
                         episodes_since_push += 1
                         self._needs_push.set()
-                        logger.info("Episode saved (total: %d)", dataset.num_episodes)
+                        logger.info(
+                            "Episode saved (total: %d, elapsed: %.1fs)",
+                            dataset.num_episodes,
+                            elapsed,
+                        )
+                        log_say(f"Episode {dataset.num_episodes} saved", play_sounds)
 
                         if episodes_since_push >= self.config.upload_every_n_episodes:
                             self._background_push(dataset, cfg)
@@ -472,6 +510,7 @@ class DAggerStrategy(RolloutStrategy):
                         precise_sleep(sleep_t)
 
             finally:
+                logger.info("DAgger continuous control loop ended — pausing engine")
                 engine.pause()
                 # TODO(Steven): either enforce this (meaning all teleop must implement these methods) or
                 # user is responsible for moving the teleop to the same position as the robot when starting the correction.
@@ -480,6 +519,7 @@ class DAggerStrategy(RolloutStrategy):
                     with self._episode_lock:
                         dataset.save_episode()
                     self._needs_push.set()
+                    logger.info("Final in-progress episode saved")
 
     # ------------------------------------------------------------------
     # Corrections-only mode (record_autonomous=False)
@@ -505,6 +545,7 @@ class DAggerStrategy(RolloutStrategy):
         control_interval = interpolator.get_control_interval(cfg.fps)
         record_stride = max(1, cfg.interpolation_multiplier)
         task_str = cfg.dataset.single_task if cfg.dataset else cfg.task
+        play_sounds = cfg.play_sounds
 
         engine.reset()
         interpolator.reset()
@@ -517,6 +558,9 @@ class DAggerStrategy(RolloutStrategy):
         last_action: dict[str, Any] | None = None
         record_tick = 0
         recorded = 0
+        logger.info(
+            "DAgger corrections-only recording started (target: %d episodes)", self.config.num_episodes
+        )
 
         with VideoEncodingManager(dataset):
             try:
@@ -540,11 +584,17 @@ class DAggerStrategy(RolloutStrategy):
                                 dataset.save_episode()
                             recorded += 1
                             self._needs_push.set()
-                            logger.info("Episode %d saved", recorded)
+                            logger.info(
+                                "Correction %d/%d saved",
+                                recorded,
+                                self.config.num_episodes,
+                            )
+                            log_say(f"Correction {recorded} saved", play_sounds)
 
                     # On-demand upload
                     if events.upload_requested.is_set():
                         events.upload_requested.clear()
+                        logger.info("Upload requested by user")
                         self._background_push(dataset, cfg)
 
                     phase = events.phase
@@ -558,6 +608,7 @@ class DAggerStrategy(RolloutStrategy):
                         robot_action_to_send = ctx.processors.robot_action_processor((processed_teleop, obs))
                         robot.send_action(robot_action_to_send)
                         last_action = robot_action_to_send
+                        self._log_telemetry(obs_processed, processed_teleop, ctx.runtime)
 
                         obs_frame = build_dataset_frame(features, obs_processed, prefix=OBS_STR)
                         action_frame = build_dataset_frame(features, processed_teleop, prefix=ACTION)
@@ -586,6 +637,7 @@ class DAggerStrategy(RolloutStrategy):
 
                         action_dict = send_next_action(obs_processed, obs, ctx, interpolator)
                         if action_dict is not None:
+                            self._log_telemetry(obs_processed, action_dict, ctx.runtime)
                             last_action = ctx.processors.robot_action_processor((action_dict, obs))
 
                     dt = time.perf_counter() - loop_start
@@ -593,6 +645,7 @@ class DAggerStrategy(RolloutStrategy):
                         precise_sleep(sleep_t)
 
             finally:
+                logger.info("DAgger corrections-only loop ended — pausing engine")
                 engine.pause()
                 # TODO(Steven): either enforce this (meaning all teleop must implement these methods) or
                 # user is responsible for moving the teleop to the same position as the robot when starting the correction.
@@ -601,6 +654,7 @@ class DAggerStrategy(RolloutStrategy):
                     with self._episode_lock:
                         dataset.save_episode()
                     self._needs_push.set()
+                    logger.info("Final in-progress episode saved")
 
     # ------------------------------------------------------------------
     # State-machine transition side-effects
@@ -616,7 +670,9 @@ class DAggerStrategy(RolloutStrategy):
         teleop: Teleoperator,
     ) -> None:
         """Execute side-effects for a validated phase transition."""
+        logger.info("Phase transition: %s -> %s", old_phase.value, new_phase.value)
         if old_phase == DAggerPhase.AUTONOMOUS and new_phase == DAggerPhase.PAUSED:
+            logger.info("Pausing engine — robot holds position")
             engine.pause()
             obs = robot.get_observation()
             _robot_pos = {
@@ -627,12 +683,13 @@ class DAggerStrategy(RolloutStrategy):
             # _teleop_smooth_move_to(teleop, robot_pos, duration_s=2.0, fps=50)
 
         elif new_phase == DAggerPhase.CORRECTING:
+            logger.info("Entering correction mode — human teleop control")
             # TODO(Steven): either enforce this (meaning all teleop must implement these methods) or
             # user is responsible for moving the teleop to the same position as the robot when starting the correction.
             # teleop.disable_torque()
-            pass
 
         elif new_phase == DAggerPhase.AUTONOMOUS:
+            logger.info("Resuming autonomous mode — resetting engine and interpolator")
             interpolator.reset()
             engine.reset()
             engine.resume()
@@ -645,24 +702,32 @@ class DAggerStrategy(RolloutStrategy):
         """Queue a Hub push on the single-worker executor.
 
         The executor's max_workers=1 guarantees at most one push runs at
-        a time; submitted tasks are queued rather than dropped.
+        a time; submitted tasks are queued rather than dropped.  Pushes
+        are blocked while the operator is mid-correction to avoid
+        uploading a partially-recorded episode.
         """
         if self._push_executor is None:
             return
 
+        if self._events.phase == DAggerPhase.CORRECTING:
+            logger.info("Skipping push — correction in progress")
+            return
+
         if self._pending_push is not None and not self._pending_push.done():
             logger.info("Previous push still in progress; queueing next")
 
         def _push():
             try:
                 with self._episode_lock:
-                    dataset.push_to_hub(
+                    if safe_push_to_hub(
+                        dataset,
                         tags=cfg.dataset.tags if cfg.dataset else None,
                         private=cfg.dataset.private if cfg.dataset else False,
-                    )
+                    ):
-                self._needs_push.clear()
+                        self._needs_push.clear()
-                logger.info("Background push to hub complete")
+                        logger.info("Background push to hub complete")
             except Exception as e:
                 logger.error("Background push failed: %s", e)
 
         self._pending_push = self._push_executor.submit(_push)
+        logger.info("Background push task submitted")

src/lerobot/rollout/strategies/highlight.py

@@ -30,11 +30,12 @@ from lerobot.utils.constants import ACTION, OBS_STR
 from lerobot.utils.feature_utils import build_dataset_frame
 from lerobot.utils.import_utils import _pynput_available, require_package
 from lerobot.utils.robot_utils import precise_sleep
+from lerobot.utils.utils import log_say
 
 from ..configs import HighlightStrategyConfig
 from ..context import RolloutContext
 from ..ring_buffer import RolloutRingBuffer
-from .core import RolloutStrategy, send_next_action
+from .core import RolloutStrategy, safe_push_to_hub, send_next_action
 
 PYNPUT_AVAILABLE = _pynput_available
 keyboard = None
@@ -91,6 +92,11 @@ class HighlightStrategy(RolloutStrategy):
         )
 
         self._push_executor = ThreadPoolExecutor(max_workers=1, thread_name_prefix="highlight-push")
+        logger.info(
+            "Ring buffer initialized (max_seconds=%.0f, max_memory=%.0fMB)",
+            self.config.ring_buffer_seconds,
+            self.config.ring_buffer_max_memory_mb,
+        )
         self._setup_keyboard(ctx.runtime.shutdown_event)
         logger.info(
             "Highlight strategy ready (buffer=%.0fs, save='%s', push='%s')",
@@ -112,9 +118,11 @@ class HighlightStrategy(RolloutStrategy):
         control_interval = interpolator.get_control_interval(cfg.fps)
 
         engine.resume()
+        play_sounds = cfg.play_sounds
 
         start_time = time.perf_counter()
         task_str = cfg.dataset.single_task if cfg.dataset else cfg.task
+        logger.info("Highlight strategy recording started (press '%s' to save)", self.config.save_key)
 
         with VideoEncodingManager(dataset):
             try:
@@ -122,6 +130,7 @@ class HighlightStrategy(RolloutStrategy):
                     loop_start = time.perf_counter()
 
                     if cfg.duration > 0 and (time.perf_counter() - start_time) >= cfg.duration:
+                        logger.info("Duration limit reached (%.0fs)", cfg.duration)
                         break
 
                     obs = robot.get_observation()
@@ -134,6 +143,7 @@ class HighlightStrategy(RolloutStrategy):
                     action_dict = send_next_action(obs_processed, obs, ctx, interpolator)
 
                     if action_dict is not None:
+                        self._log_telemetry(obs_processed, action_dict, ctx.runtime)
                         obs_frame = build_dataset_frame(features, obs_processed, prefix=OBS_STR)
                         action_frame = build_dataset_frame(features, action_dict, prefix=ACTION)
                         frame = {**obs_frame, **action_frame, "task": task_str}
@@ -159,11 +169,16 @@ class HighlightStrategy(RolloutStrategy):
                             else:
                                 dataset.add_frame(frame)
                                 dataset.save_episode()
-                                logger.info("Episode saved")
+                                logger.info("Episode saved (total: %d)", dataset.num_episodes)
+                                log_say(
+                                    f"Episode {dataset.num_episodes} saved",
+                                    play_sounds,
+                                )
                                 self._recording_live.clear()
 
                         if self._push_requested.is_set():
                             self._push_requested.clear()
+                            logger.info("Push requested by user")
                             self._background_push(dataset, cfg)
 
                         if self._recording_live.is_set():
@@ -176,26 +191,39 @@ class HighlightStrategy(RolloutStrategy):
                         precise_sleep(sleep_t)
 
             finally:
+                logger.info("Highlight control loop ended")
                 if self._recording_live.is_set():
+                    logger.info("Saving in-progress live episode")
                     with contextlib.suppress(Exception):
                         dataset.save_episode()
 
     def teardown(self, ctx: RolloutContext) -> None:
         """Stop listeners, finalise the dataset, and disconnect hardware."""
+        play_sounds = ctx.runtime.cfg.play_sounds
+        logger.info("Stopping highlight recording")
+        log_say("Stopping highlight recording", play_sounds)
+
         if self._listener is not None:
+            logger.info("Stopping keyboard listener")
             self._listener.stop()
 
         if self._push_executor is not None:
+            logger.info("Shutting down push executor (waiting for pending pushes)...")
             self._push_executor.shutdown(wait=True)
             self._push_executor = None
 
         if ctx.data.dataset is not None:
+            logger.info("Finalizing dataset...")
             ctx.data.dataset.finalize()
             if ctx.runtime.cfg.dataset and ctx.runtime.cfg.dataset.push_to_hub:
-                ctx.data.dataset.push_to_hub(
+                logger.info("Pushing final dataset to hub...")
+                if safe_push_to_hub(
+                    ctx.data.dataset,
                     tags=ctx.runtime.cfg.dataset.tags,
                     private=ctx.runtime.cfg.dataset.private,
-                )
+                ):
+                    logger.info("Dataset uploaded to hub")
+                    log_say("Dataset uploaded to hub", play_sounds)
 
         self._teardown_hardware(ctx.hardware)
         logger.info("Highlight strategy teardown complete")
@@ -222,6 +250,7 @@ class HighlightStrategy(RolloutStrategy):
 
             self._listener = keyboard.Listener(on_press=on_press)
             self._listener.start()
+            logger.info("Keyboard listener started (save='%s', push='%s', ESC=stop)", save_key, push_key)
         except ImportError:
             logger.warning("pynput not available — keyboard listener disabled")
 
@@ -235,12 +264,14 @@ class HighlightStrategy(RolloutStrategy):
 
         def _push():
             try:
-                dataset.push_to_hub(
+                if safe_push_to_hub(
+                    dataset,
                     tags=cfg.dataset.tags if cfg.dataset else None,
                     private=cfg.dataset.private if cfg.dataset else False,
-                )
+                ):
-                logger.info("Background push to hub complete")
+                    logger.info("Background push to hub complete")
             except Exception as e:
                 logger.error("Background push failed: %s", e)
 
         self._pending_push = self._push_executor.submit(_push)
+        logger.info("Background push task submitted")

src/lerobot/rollout/strategies/sentry.py

@@ -23,13 +23,15 @@ from concurrent.futures import Future, ThreadPoolExecutor
 from threading import Event, Lock
 
 from lerobot.datasets import VideoEncodingManager
+from lerobot.datasets.utils import DEFAULT_VIDEO_FILE_SIZE_IN_MB
 from lerobot.utils.constants import ACTION, OBS_STR
 from lerobot.utils.feature_utils import build_dataset_frame
 from lerobot.utils.robot_utils import precise_sleep
+from lerobot.utils.utils import log_say
 
 from ..configs import SentryStrategyConfig
 from ..context import RolloutContext
-from .core import RolloutStrategy, send_next_action
+from .core import RolloutStrategy, estimate_max_episode_seconds, safe_push_to_hub, send_next_action
 
 logger = logging.getLogger(__name__)
 
@@ -37,9 +39,15 @@ logger = logging.getLogger(__name__)
 class SentryStrategy(RolloutStrategy):
     """Continuous autonomous rollout with always-on recording.
 
-    Episodes are auto-rotated every ``episode_duration_s`` seconds.  The
+    Episode duration is derived from camera resolution, FPS, and
-    dataset is pushed to the Hub via a bounded single-worker executor so
+    ``DEFAULT_VIDEO_FILE_SIZE_IN_MB`` so that each saved episode
-    no push is ever silently dropped and exactly one push runs at a time.
+    produces a video file that has crossed the chunk-size boundary.
+    This keeps ``push_to_hub`` efficient — it uploads complete video
+    files rather than re-uploading a still-growing one.
+
+    The dataset is pushed to the Hub via a bounded single-worker executor
+    so no push is ever silently dropped and exactly one push runs at a
+    time.
 
     Policy state (hidden state, RTC queue) intentionally persists across
     episode boundaries — Sentry slices one continuous rollout, the robot
@@ -62,9 +70,13 @@ class SentryStrategy(RolloutStrategy):
         """Initialise the inference engine and background push executor."""
         self._init_engine(ctx)
         self._push_executor = ThreadPoolExecutor(max_workers=1, thread_name_prefix="sentry-push")
+        target_mb = self.config.target_video_file_size_mb or DEFAULT_VIDEO_FILE_SIZE_IN_MB
+        self._episode_duration_s = estimate_max_episode_seconds(
+            ctx.data.dataset_features, ctx.runtime.cfg.fps, target_size_mb=target_mb
+        )
         logger.info(
             "Sentry strategy ready (episode_duration=%.0fs, upload_every=%d eps)",
-            self.config.episode_duration_s,
+            self._episode_duration_s,
             self.config.upload_every_n_episodes,
         )
 
@@ -80,11 +92,14 @@ class SentryStrategy(RolloutStrategy):
         control_interval = interpolator.get_control_interval(cfg.fps)
 
         engine.resume()
+        play_sounds = cfg.play_sounds
+        episode_duration_s = self._episode_duration_s
 
         start_time = time.perf_counter()
         episode_start = time.perf_counter()
         episodes_since_push = 0
         task_str = cfg.dataset.single_task if cfg.dataset else cfg.task
+        logger.info("Sentry recording started (episode_duration=%.0fs)", episode_duration_s)
 
         with VideoEncodingManager(dataset):
             try:
@@ -92,6 +107,7 @@ class SentryStrategy(RolloutStrategy):
                     loop_start = time.perf_counter()
 
                     if cfg.duration > 0 and (time.perf_counter() - start_time) >= cfg.duration:
+                        logger.info("Duration limit reached (%.0fs)", cfg.duration)
                         break
 
                     obs = robot.get_observation()
@@ -104,6 +120,7 @@ class SentryStrategy(RolloutStrategy):
                     action_dict = send_next_action(obs_processed, obs, ctx, interpolator)
 
                     if action_dict is not None:
+                        self._log_telemetry(obs_processed, action_dict, ctx.runtime)
                         obs_frame = build_dataset_frame(features, obs_processed, prefix=OBS_STR)
                         action_frame = build_dataset_frame(features, action_dict, prefix=ACTION)
                         frame = {**obs_frame, **action_frame, "task": task_str}
@@ -113,8 +130,12 @@ class SentryStrategy(RolloutStrategy):
                         # ``add_frame`` does not need ``_episode_lock``.
                         dataset.add_frame(frame)
 
+                    # Episode rotation derived from video file-size target.
+                    # The duration is a conservative estimate so the actual
+                    # video has crossed DEFAULT_VIDEO_FILE_SIZE_IN_MB by now,
+                    # keeping push_to_hub efficient (uploads complete files).
                     elapsed = time.perf_counter() - episode_start
-                    if elapsed >= self.config.episode_duration_s:
+                    if elapsed >= episode_duration_s:
                         # ``save_episode`` finalises the in-progress episode and
                         # flushes it to disk; ``_episode_lock`` serialises this with
                         # ``push_to_hub`` (run in the background executor) so the
@@ -123,7 +144,12 @@ class SentryStrategy(RolloutStrategy):
                             dataset.save_episode()
                         episodes_since_push += 1
                         self._needs_push.set()
-                        logger.info("Episode saved (total: %d)", dataset.num_episodes)
+                        logger.info(
+                            "Episode saved (total: %d, elapsed: %.1fs)",
+                            dataset.num_episodes,
+                            elapsed,
+                        )
+                        log_say(f"Episode {dataset.num_episodes} saved", play_sounds)
 
                         if episodes_since_push >= self.config.upload_every_n_episodes:
                             self._background_push(dataset, cfg)
@@ -136,6 +162,7 @@ class SentryStrategy(RolloutStrategy):
                         precise_sleep(sleep_t)
 
             finally:
+                logger.info("Sentry control loop ended — saving final episode")
                 with contextlib.suppress(Exception):
                     with self._episode_lock:
                         dataset.save_episode()
@@ -143,18 +170,28 @@ class SentryStrategy(RolloutStrategy):
 
     def teardown(self, ctx: RolloutContext) -> None:
         """Flush pending pushes, finalise the dataset, and disconnect hardware."""
+        play_sounds = ctx.runtime.cfg.play_sounds
+        logger.info("Stopping sentry recording")
+        log_say("Stopping sentry recording", play_sounds)
+
         # Flush any queued/running push cleanly.
         if self._push_executor is not None:
+            logger.info("Shutting down push executor (waiting for pending pushes)...")
             self._push_executor.shutdown(wait=True)
             self._push_executor = None
 
         if ctx.data.dataset is not None:
+            logger.info("Finalizing dataset...")
             ctx.data.dataset.finalize()
             if self._needs_push.is_set() and ctx.runtime.cfg.dataset and ctx.runtime.cfg.dataset.push_to_hub:
-                ctx.data.dataset.push_to_hub(
+                logger.info("Pushing final dataset to hub...")
+                if safe_push_to_hub(
+                    ctx.data.dataset,
                     tags=ctx.runtime.cfg.dataset.tags,
                     private=ctx.runtime.cfg.dataset.private,
-                )
+                ):
+                    logger.info("Dataset uploaded to hub")
+                    log_say("Dataset uploaded to hub", play_sounds)
 
         self._teardown_hardware(ctx.hardware)
         logger.info("Sentry strategy teardown complete")
@@ -174,13 +211,15 @@ class SentryStrategy(RolloutStrategy):
         def _push():
             try:
                 with self._episode_lock:
-                    dataset.push_to_hub(
+                    if safe_push_to_hub(
+                        dataset,
                         tags=cfg.dataset.tags if cfg.dataset else None,
                         private=cfg.dataset.private if cfg.dataset else False,
-                    )
+                    ):
-                self._needs_push.clear()
+                        self._needs_push.clear()
-                logger.info("Background push to hub complete")
+                        logger.info("Background push to hub complete")
             except Exception as e:
                 logger.error("Background push failed: %s", e)
 
         self._pending_push = self._push_executor.submit(_push)
+        logger.info("Background push task submitted")

src/lerobot/scripts/lerobot_record.py

@@ -484,7 +484,10 @@ def record(
             listener.stop()
 
         if cfg.dataset.push_to_hub:
-            dataset.push_to_hub(tags=cfg.dataset.tags, private=cfg.dataset.private)
+            if dataset and dataset.num_episodes > 0:
+                dataset.push_to_hub(tags=cfg.dataset.tags, private=cfg.dataset.private)
+            else:
+                logging.warning("No episodes saved — skipping push to hub")
 
         log_say("Exiting", cfg.play_sounds)
     return dataset

src/lerobot/scripts/lerobot_rollout.py

@@ -44,7 +44,6 @@ Usage examples::
     # Sentry mode (continuous recording)
     lerobot-rollout \\
         --strategy.type=sentry \\
-        --strategy.episode_duration_s=120 \\
         --strategy.upload_every_n_episodes=5 \\
         --policy.path=lerobot/pi0_base \\
         --inference.type=rtc \\
@@ -82,9 +81,7 @@ from lerobot.robots import (  # noqa: F401
     so_follower,
     unitree_g1 as unitree_g1_robot,
 )
-from lerobot.rollout.configs import RolloutConfig
+from lerobot.rollout import RolloutConfig, build_rollout_context, create_strategy
-from lerobot.rollout.context import build_rollout_context
-from lerobot.rollout.strategies import create_strategy
 from lerobot.teleoperators import (  # noqa: F401
     Teleoperator,
     TeleoperatorConfig,
@@ -102,6 +99,7 @@ from lerobot.teleoperators import (  # noqa: F401
 from lerobot.utils.import_utils import register_third_party_plugins
 from lerobot.utils.process import ProcessSignalHandler
 from lerobot.utils.utils import init_logging
+from lerobot.utils.visualization_utils import init_rerun
 
 logger = logging.getLogger(__name__)
 
@@ -111,6 +109,10 @@ def rollout(cfg: RolloutConfig):
     """Main entry point for policy deployment."""
     init_logging()
 
+    if cfg.display_data:
+        logger.info("Initializing Rerun visualization (ip=%s, port=%s)", cfg.display_ip, cfg.display_port)
+        init_rerun(session_name="rollout", ip=cfg.display_ip, port=cfg.display_port)
+
     signal_handler = ProcessSignalHandler(use_threads=True, display_pid=False)
     shutdown_event = signal_handler.shutdown_event
 
@@ -118,10 +120,17 @@ def rollout(cfg: RolloutConfig):
     ctx = build_rollout_context(cfg, shutdown_event)
 
     strategy = create_strategy(cfg.strategy)
-    logger.info("Strategy: %s", cfg.strategy.type)
+    logger.info("Rollout strategy: %s", cfg.strategy.type)
+    logger.info(
+        "Robot: %s | FPS: %.0f | Duration: %s",
+        cfg.robot.type if cfg.robot else "?",
+        cfg.fps,
+        f"{cfg.duration}s" if cfg.duration > 0 else "infinite",
+    )
 
     try:
         strategy.setup(ctx)
+        logger.info("Rollout setup complete, starting rollout...")
         strategy.run(ctx)
     except KeyboardInterrupt:
         logger.info("Interrupted by user")