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lerobot/examples/isaac_teleop_to_so101/isaac_teleop/clutch.py
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Caroline Pascal 293a8d9a77 feat(examples): add Isaac Teleop → SO-101 teleoperation and dataset recording example (#3927)
* Add Isaac Teleop SO-101 leader-arm teleoperator

Add the NVIDIA Isaac Teleop teleoperator scaffolding and its first device:
SO101LeaderArm, a back-drivable SO-101 leader arm on Isaac Teleop's generic
joint-space device path. It reads the leader's joints from the so101_leader
plugin via JointStateSource and emits follower-ready {joint}.pos (rad2deg arm,
gripper -> RANGE_0_100) for direct 1:1 joint drive.

- IsaacTeleopTeleoperator base + IsaacTeleopConfig (shared session/CloudXR config)
- SO101LeaderArm / SO101LeaderArmConfig and leader_joints_to_robot_action
- examples/isaac_teleop_to_so101/teleoperate_leader.py example
- pure-numpy conversion tests
- isaac-teleop optional extra + NVIDIA PyPI index in pyproject

* Add Isaac Teleop XR controller teleoperator for SO-101

Add end-to-end XR (VR) controller teleoperation of an SO-101 follower arm via
the NVIDIA Isaac Teleop stack, layered on the Isaac Teleop scaffolding.

Teleoperator (src/lerobot/teleoperators/isaac_teleop/):
- XRController / XRControllerConfig: connect to the CloudXR runtime, auto-launch
  the Isaac Teleop session, and expose get_action() emitting the raw base-frame
  grip pose, squeeze, and trigger.
- MapXRControllerActionToRobotAction: stateless per-frame mapper from the XR
  action to the IK input contract (absolute ee.x/y/z, ee.gripper_pos, wrist_roll).
- OverwriteWristRollFromAngle: post-IK step writing the operator wrist-roll [rad]
  onto wrist_roll.pos [deg], recovering the under-determined roll DOF.

Example (examples/isaac_teleop_to_so101/):
- teleoperate.py: thin absolute-pose IK pipeline with an in-loop clutch (engage
  latch + 1:1 delta rebase of position and orientation), EEBoundsAndSafety, and
  InverseKinematicsEEToJoints; slews to a recorded home on startup.
- record_reset_pose.py / download_assets.py / webxr.env / .gitignore.

Also:
- Extend robot_kinematic_processor.py with EEBoundsAndSafety and
  InverseKinematicsEEToJoints.
- Add XRControllerConfig + base_T_anchor to the Isaac Teleop config.
- Add docs/source/isaac_teleop.mdx and the _toctree entry.
- Add unit tests for the CloudXR launcher and the XR controller processor.

* Unify Isaac Teleop SO-101 scripts behind a mandatory device selector

Merge teleoperate.py (XR controller: clutch + soft-orientation IK) and
teleoperate_leader.py (SO-101 leader arm: 1:1 joint mirror) into a single
teleoperate.py driven by a `lerobot-teleoperate`-style draccus CLI: a follower
`--robot.*` and an input `--teleop.*`, where `--teleop.type` (xr_controller |
so101_leader) selects the Isaac device.

Uses a "dispatch, don't merge" shape: per-device setup_xr/setup_leader build a
Device bundle (compute / startup / cleanup / command); a shared slew() takes a
per-step target callable (XR a fixed reset pose, leader a live re-read so the
1:1 handoff stays continuous); one device-branchless outer loop runs both, with
compute() -> None meaning "hold at the measured pose" (XR disengaged or leader
stale). The entrypoint is @parser.wrap()'d over a TeleoperateConfig dataclass and
dispatches on the parsed config type; device knobs ride on --teleop.* (the leader
serial port is --teleop.port, forwarded to the plugin) and loop/launch knobs are
top-level (--launch_plugin=<path> collapses the old --launch-plugin/--plugin-bin
pair; --reset_to_origin/--align/--dry_run).

To let the Isaac devices claim the natural --teleop.type names without colliding
with the serial so101_leader of lerobot-teleoperate, give IsaacTeleopConfig its
own draccus choice registry (own _choice_registry, decoupled from the global
TeleoperatorConfig one) and register XRControllerConfig as "xr_controller" and
SO101LeaderArmConfig as "so101_leader" there; the example types its teleop field
as IsaacTeleopConfig so the choices resolve against that scoped registry. These
devices drive the bespoke clutch/IK/align loop and are not routed through
make_teleoperator_from_config, so dropping them from the global registry is inert.

YAGNI sweep of the commit train: delete the orphaned OverwriteWristRollFromAngle
(wrist_roll_processor.py) plus its export and tests -- no producer emits
wrist_roll; the live XR path uses orientation-weight IK on the 5-DOF arm by
design. Kept the load-bearing knobs (orientation_weight, raise_on_jump,
base_T_anchor) and the optional reset-pose recorder. Updated isaac_teleop.mdx
for the unified entrypoint and excised the stale roll-retargeter prose.

Net LOC down (two scripts 714 lines -> one), in-loop device branches reduced to
zero. Planned and reviewed via a 6-persona multi-agent panel (3-round planning
convergence + 2-round review). Verification (isaacteleop/placo not installable
here, so the device classes cannot connect, but their config dataclasses and the
script import fine via deferred imports): the teleoperators test suite passes
(45 passed, 2 skipped), draccus parsing of both target command lines yields the
right config subclass with scoped --teleop.type, --help renders the scoped
choices, the serial so101_leader stays in the global registry, and ruff
check/format are green.

Signed-off-by: Jiwen Cai <jiwenc@nvidia.com>

* Add Isaac Teleop SO-101 dataset recording script

record.py records a LeRobot dataset while driving the SO-101 follower
with either Isaac Teleop device (--teleop.type=xr_controller |
so101_leader), mirroring teleoperate.py's device dispatch.

* Extract shared Isaac Teleop SO-101 example infra into common.py

teleoperate.py and record.py both built the per-device pipeline and ran the
same read -> compute -> hold-when-idle -> sleep loop, with record.py importing
internals from teleoperate.py. Move the shared device/loop infrastructure
(Device, slew, Clutch, setup_xr/setup_leader + leader helpers, reset infra and
constants) into a new common.py, and add build_device() + hold_action() to
collapse the connect/dispatch/startup and idle-hold glue duplicated in both
entry points. The setup functions now type their config against a LoopConfig
Protocol, so common.py is decoupled from either CLI; both import from it.

Also rename record_reset_pose.py -> override_reset_pose.py so it is not confused
with record.py, and update the doc references.

* Add stdin keyboard backend so recording shortcuts work over SSH/headless

lerobot's init_keyboard_listener() uses pynput, which hooks GLOBAL key events
from the display server. Over SSH, under Wayland, or on a headless box with only a
TTY, keystrokes go to the terminal's stdin instead, so the listener never fires and
the Right/Left/Esc recording shortcuts silently do nothing.

Add a stdin (termios) keyboard backend to the example's common.py and an
init_keyboard_listener() that prefers it whenever stdin is an interactive TTY
(works over SSH / Wayland / headless-with-tty), falling back to lerobot's
pynput/headless listener for GUI launches with no controlling terminal. Selectable
via LEROBOT_KEYBOARD_BACKEND={auto,stdin,pynput,none}. The backend keeps ISIG so
Ctrl-C still works and always restores the terminal (on stop() and via atexit).
record.py now sources init_keyboard_listener from common; the Right/Left/Esc -> flag
mapping and the (listener, events) contract are unchanged.

Also convert record.py's loop_kwargs to a dict literal (ruff C408).

* Wait for the XR headset to connect before driving the arm

On the xr_controller path the example connected CloudXR and immediately ran the
reset slew + control loop, even if no headset was connected — the arm moved before
the operator was in VR, and get_action() just returned zeros so the clutch never
engaged.

Add an is_tracking property to XRController (set from the controller stream's
optional group, mirroring SO101LeaderArm) and a _wait_for_xr_controller() helper in
common.py that prints connection instructions (CloudXR web client URL + this
workstation's candidate IPv4s, with loopback/link-local and virtual/bridge/USB-gadget
interfaces filtered out) and polls until the controllers stream (indefinite, 15s
reminder, Ctrl-C to abort). setup_xr.startup() now connects, waits for the headset,
THEN runs the reset slew and seeds the clutch — so the arm only moves once the
operator is connected and watching. Mirrors the leader path's _wait_for_leader; both
record.py and teleoperate.py inherit it via the shared setup_xr.

* Address review feedback on the Isaac Teleop -> SO-101 example

Review-response and CI fixes for the Isaac Teleop -> SO-101 example.

- Move the XR Clutch into src/lerobot/teleoperators/isaac_teleop/clutch.py
  (pure numpy + Rotation, no isaacteleop import), export it, and add
  tests/teleoperators/test_clutch.py.
- Drop the vendored stdin keyboard listener; record.py uses a small terminal-
  first wrapper over upstream's TerminalKeyListener (works over SSH even with a
  local X display), falling back to upstream init_keyboard_listener otherwise.
- record.py: pass rgb_encoder/depth_encoder to LeRobotDataset create()/resume()
  (upstream removed camera_encoder), fixing the AttributeError at record time.
- build_device: derive motor names from robot.action_features instead of
  robot.bus (supports non-bus robots), and disconnect the follower if any step
  after connect() fails so a failed setup never leaks the connection.
- Read leader joints by the group's declared names (_joints_group_to_rad)
  instead of positionally, so a layout mismatch can't silently mirror the wrong
  DOF onto the follower; add tests including a reversed-layout group.
- base.py: hoist `from pathlib import Path` to module scope; only the
  isaacteleop CloudXRLauncher import stays lazy (optional dep).
- Trim the common.py module docstring and point to docs/source/isaac_teleop.mdx.
- default.env: correct the NV_DEVICE_PROFILE comment (auto-webrtc is the default;
  this file overrides to Quest3, which works for both Quest 3 and Pico 4).
- download_assets.py: correct the RAW_BASE comment (tracks main, not pinned) and
  add `# nosec B310` next to the existing `# noqa: S310` for the bandit hook.
- uv.lock: add the isaac-teleop extra's deps so `uv sync --locked` matches
  pyproject; regenerated with uv 0.8.0 to keep lockfile revision 2 (CI's uv).
- isaac_teleop.mdx: prettier formatting.

* fix(.gitignore): removing .gitignore and using lerobot cache folder instead to store local user files

* chore(docstrings): reducing docstrings in default.env

* feat(URDF): cleaning up and simplifying the URDF download procedure

* feat(robot guard): adding a guard in case an unsupported robot type is provided (so-arms only)

* fix(imports): enforcing a python module structure to simplify imports

* feat(safe read): extending the motor bus safe read rationale to reset pose setting

* chore(trim): trimming lenghty comments and docstrings

* fix(deps): use isaacteleop [retargeters-lite] extra to unblock aarch64 (DGX Spark) (#3933)

* fix(deps): drop isaacteleop [retargeters] extra to unblock aarch64

The [retargeters] extra pulls dex-retargeting (pins numpy<2.0, conflicting
with lerobot's numpy>=2.0) and nlopt>=2.8 (no aarch64 wheels), making
lerobot[isaac-teleop] unresolvable on ARM (DGX Spark, Jetson Thor, GH200)
and over-constrained on numpy everywhere else.

The LeRobot teleoperators only import isaacteleop.retargeting_engine,
isaacteleop.cloudxr and isaacteleop.teleop_session_manager, all shipped in
the base wheel (requires only numpy>=1.23), so the extra is unused.

Verified on DGX Spark (aarch64, Python 3.12): resolves and installs with
isaacteleop 1.3.131 + numpy 2.2.6; all imported symbols load.

* fix(deps): use isaacteleop [retargeters-lite] extra for aarch64 support

Pin to isaacteleop ~=1.3.131 (the release that added ARM64/aarch64 support)
and swap the full [retargeters] extra for the new [retargeters-lite] one
(scipy-only). The full extra drags in dex-retargeting (pins numpy<2,
conflicting with lerobot's numpy>=2.0) and nlopt>=2.8 (no aarch64 wheels),
making lerobot[isaac-teleop] unresolvable on ARM hosts (DGX Spark, Jetson
Thor, GH200) and over-constrained on numpy everywhere else.

The LeRobot teleoperators only import isaacteleop.retargeting_engine,
isaacteleop.cloudxr and isaacteleop.teleop_session_manager — all covered
by the base wheel + retargeters-lite.

Verified on DGX Spark (aarch64, Python 3.12/3.13): resolves and installs
with isaacteleop 1.3.131 + numpy 2.2.6 + scipy 1.18.

* feat(deps): re-add full [retargeters] extra gated to x86_64

Keep the dex-retargeting/nlopt-based retargeters available on x86_64 (where
their wheels exist) via an environment marker, while ARM hosts (DGX Spark,
Jetson Thor, GH200) resolve with base + [retargeters-lite] only.

Verified: uv lock resolves on both platforms; on aarch64 the compile
excludes nlopt/dex-retargeting, on x86_64 they are included.

---------

Co-authored-by: Johnny Nunez <22727137+johnnynunez@users.noreply.github.com>

* chore(docstrings): trimming latest docstrings

* chore(teleop): move isaac-teleop to examples + update docs + add readme with installation notes

* chore(deps): restore uv.lock

* fix(example: isaac teleop parsing config

* fix(examples): isaac atomic-gripper controller

* feat(Examples): isaac-teleop holdlatch

* chore(examples): some other minor improvements for isaac-teleop

* chore(examples): top-level imports isaac-teleop

* chore(Examples): address ai review isaac-teleop

---------

Signed-off-by: Jiwen Cai <jiwenc@nvidia.com>
Co-authored-by: Jiwen Cai <jiwenc@nvidia.com>
Co-authored-by: Johnny <johnnync13@gmail.com>
Co-authored-by: Johnny Nunez <22727137+johnnynunez@users.noreply.github.com>
Co-authored-by: Steven Palma <steven.palma@huggingface.co>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
2026-07-05 20:56:26 +02:00

103 lines
4.9 KiB
Python

#!/usr/bin/env python
# Copyright 2026 NVIDIA Corporation and 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.
"""Engage-relative clutch for the XR -> SO-101 teleop loop.
Turns the raw controller grip pose into an absolute base-frame EE target, so the XR
device can stay a thin raw-pose reader. Pure numpy + the local ``Rotation`` helper (no
``isaacteleop``), so it is unit-testable without the XR runtime.
"""
from __future__ import annotations
import numpy as np
from lerobot.utils.rotation import Rotation
class Clutch:
"""Engage-relative clutch for both position AND orientation.
Latch an origin on engage, then track the base-frame delta from it, applied
independently to position and orientation. State:
- ``_last_commanded_pos`` / ``_last_commanded_rot``: last commanded EE pose; held
while disengaged so the arm freezes where it was left.
- ``_home_pos`` / ``_home_rot``: latched on engage — the EE pose the delta applies to.
The position comes from the arm's MEASURED pose when the caller provides it (so an
arm that moved while disengaged is not snapped back to a stale command); the
orientation always comes from the last commanded rotation (see NOTE below).
- ``_origin_pos`` / ``_origin_rot``: latched on engage — the controller pose the delta
is measured against.
Each engaged frame :meth:`rebase` returns::
pos = home_pos + (grip_pos - origin_pos) # 1:1 controller -> EE translation
rot = (R_ctrl @ R_origin ^ -1) @ R_home # base-frame delta, left-composed
On the engage edge the output is exactly the home pose (no teleport). The orientation
delta is left-composed (base frame), so hand rotation about base Z maps to EE rotation
about base Z. A re-clutch latches a fresh home/origin.
NOTE: ``_home_rot`` is the last *commanded* orientation even when the measured pose is
supplied: the 5-DOF SO-101 tracks orientation only softly, so its measured wrist
orientation persistently differs from the command, and latching the measurement would
inject that offset into the commanded signal on every re-clutch. Position has no such
tracking gap, and there latching the measurement is what prevents the snap-back.
"""
def __init__(self, home_base_T_ee: np.ndarray): # noqa: N803
# Seed the held pose from the arm's measured startup EE pose so the first
# engage latches home there (no jump on the first squeeze).
home = np.asarray(home_base_T_ee, dtype=float)
self._last_commanded_pos = home[:3, 3].copy()
self._last_commanded_rot = Rotation.from_matrix(home[:3, :3])
self._home_pos = self._last_commanded_pos.copy()
self._home_rot = self._last_commanded_rot
self._origin_pos = np.zeros(3, dtype=float)
self._origin_rot = Rotation.from_quat(np.array([0.0, 0.0, 0.0, 1.0]))
def engage(
self,
grip_pos: np.ndarray,
grip_quat: np.ndarray,
measured_base_T_ee: np.ndarray | None = None, # noqa: N803
) -> None:
"""Latch the engage home (where the arm is now) and controller origin.
Pass ``measured_base_T_ee`` (FK of the measured joints) so the home POSITION is
where the arm physically is — if the arm moved while disengaged (gravity sag,
external contact), latching the stale last-commanded position would make the
first engaged frame command a full-speed jump back to it. The home ORIENTATION
always stays the last commanded one (see the class NOTE).
"""
if measured_base_T_ee is not None:
self._home_pos = np.asarray(measured_base_T_ee, dtype=float)[:3, 3].copy()
else:
self._home_pos = self._last_commanded_pos.copy()
self._home_rot = self._last_commanded_rot
self._origin_pos = np.asarray(grip_pos, dtype=float).copy()
self._origin_rot = Rotation.from_quat(np.asarray(grip_quat, dtype=float))
def rebase(self, grip_pos: np.ndarray, grip_quat: np.ndarray) -> tuple[np.ndarray, np.ndarray]:
"""Return the absolute base-frame EE target ``(pos [m], quat [xyzw])`` for this frame."""
pos = self._home_pos + (np.asarray(grip_pos, dtype=float) - self._origin_pos)
rot_ctrl = Rotation.from_quat(np.asarray(grip_quat, dtype=float))
rot = (rot_ctrl * self._origin_rot.inv()) * self._home_rot
self._last_commanded_pos = pos.copy()
self._last_commanded_rot = rot
return pos, rot.as_quat()