* docs(benchmarks): add benchmark integration guide and standardize benchmark docs
Add a comprehensive guide for adding new benchmarks to LeRobot, and
refactor the existing LIBERO and Meta-World docs to follow the new
standardized template.
* refactor(envs): move dispatch logic from factory into EnvConfig subclasses
Replace hardcoded if/elif chains in factory.py with create_envs() and
get_env_processors() methods on EnvConfig. New benchmarks now only need
to register a config subclass — no factory.py edits required.
Net -23 lines: factory.py shrinks from ~200 to ~70 lines of logic.
* docs(benchmarks): clean up adding-benchmarks guide for clarity
Rewrite for simpler language, better structure, and easier navigation.
Move quick-reference table to the top, fold eval explanation into
architecture section, condense the doc template to a bulleted outline.
* fix link
* fix task count
* fix(tests): fix 3 failing dispatch tests
- test_registry_all_types: skip non-EnvConfig stubs (e.g. TestPluginConfig)
- test_processors_delegation: use None instead of abstract PreTrainedConfig
- test_custom_get_env_processors_override: use DataProcessorPipeline for isinstance check (PolicyProcessorPipeline is a subscripted generic)
* fix: enable SmolVLA eval on LIBERO with custom camera mappings
- Thread camera_name_mapping from LiberoEnv config through to gym envs
- Sync features_map with camera_name_mapping in LiberoEnv.__post_init__
- Fix render() to use first available camera instead of hardcoded "image"
- Handle non-dict final_info in rollout by falling back to info["is_success"]
- Add use_peft legacy field to SmolVLAConfig for checkpoint compat
- Add defaults to GR00TN15Config init=False fields for transformers 5.3
Made-with: Cursor
* fix: use direct AutoresetMode import for gymnasium compat
Made-with: Cursor
* fix: handle gymnasium < 1.0 without AutoresetMode
Made-with: Cursor
* refactor: revert policy changes, keep env-only camera mapping fixes
- Revert GR00T N1.5 default_factory/default changes (transformers compat)
- Revert SmolVLA use_peft legacy field
- Apply ruff formatting fixes
- camera_name_mapping stays entirely in env/eval layer (no policy changes)
Made-with: Cursor
* Update docs/source/env_processor.mdx
Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>
* Update docs/source/env_processor.mdx
Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>
* Update docs/source/env_processor.mdx
Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>
* fix(eval): raise RuntimeError for unsupported final_info format (Gymnasium < 1.0)
Made-with: Cursor
* style: fix markdown code fences in env_processor.mdx
Made-with: Cursor
* docs: remove duplicate code blocks in env_processor.mdx
Made-with: Cursor
* style: revert quadruple backticks to triple (prettier compat)
* docs(env_processor): add EnvConfig subclass step and policy_cfg examples
- Add missing '### 2. Update Your EnvConfig Subclass' section with
get_env_processors() snippet
- Update factory usage example to show policy_cfg parameter and
keyword-argument style for both SmolVLA and ACT cases
* docs(env_processor): rename step 2 and fix policy_cfg examples
- Rename '### 2. Update the Factory' → '### 2. Update Your EnvConfig Subclass'
- Update factory usage examples to use keyword-argument style with
policy_cfg parameter for both SmolVLA and ACT cases
---------
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
* feat(ffmpeg): updating ffmpeg verion to 8.X
* Revert "feat(ffmpeg): updating ffmpeg verion to 8.X"
This reverts commit bb0f03185c.
* chore(pyproject): updating pyproject to fit the minimally required version of torchcodec
* chore(docs): updating doc with specific instructions for ffmpeg/torchcodec installation
* fix(typo): reverting ceiling bound on pytorch to 2.11.0
* chore(format): removing empty line
* chore(typo): fixing typo
* chore(docs): adding warning in case of torchcodec/ffmpeg version mismatch
* chore(docs): applying comments
* chore(docs): adding uv commands for evdev on WSL
* fix(typo): fixing typo
* fix(typo): fixing typos again
* chore(ruff): format
* fix(evdev install): splitting evdev install instructions between conda and uv
* chore(ruff): format
---------
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
* feat: HIL data collection, RTC interpolator, and action queue improvements
- Add Human-in-the-Loop (HIL) data collection examples (sync + RTC)
- Add HIL data collection documentation
- Add ActionInterpolator for smoother policy control at higher rates
- Integrate interpolator into lerobot-record and eval_with_real_robot
- Add action queue clear() and get_processed_left_over() methods
- Add rtc/__init__.py for cleaner imports
* docs: expand Related Work section with paper summaries
* fix: only record dataset frames at original fps, not at interpolated rate
The interpolator speeds up robot control (e.g. 2x) but dataset frames
should still be recorded at the original fps. Interpolated-only
iterations now only send actions to the robot without writing to the
dataset.
* refactor: merge HIL sync and RTC scripts into single file with --rtc.enabled toggle
Combines hil_data_collection.py and hil_data_collection_rtc.py into one
script. RTC is toggled via --rtc.enabled=true (defaults to off for sync
inference). Deletes the separate hil_data_collection_rtc.py and updates
docs to reflect the single-script usage.
* test: add ActionInterpolator test suite (29 tests)
Covers constructor validation, passthrough (multiplier=1), 2x and 3x
interpolation with exact value checks, reset/episode boundaries,
control interval calculation, multi-dim actions, and simulated
control loop integration.
* test: add ActionQueue + ActionInterpolator integration tests
Verifies the interpolator doesn't interfere with RTC's leftover chunk
tracking: queue consumption rate matches base fps regardless of
multiplier, get_left_over/get_processed_left_over only change on
queue.get(), merge preserves smooth interpolation across chunks,
and interpolator reset is independent of queue state.
* feat: register SO follower/leader configs in HIL script
Adds SOFollowerRobotConfig and SOLeaderTeleopConfig imports so
SO100/SO101 robots can be used via --robot.type=so_follower
and --teleop.type=so_leader. Updates docs accordingly.
Made-with: Cursor
* docs: remove em dashes from HIL documentation
Made-with: Cursor
* refactor: rename examples/rac to examples/hil
Updates directory name and all references in docs and script docstrings.
Made-with: Cursor
* fix: encorperate pr feedback comments
* refactor(tests): enhance ActionInterpolator test structure and add detailed docstrings
* feedback pr and test fix
* fix(test): pass correct real_delay in interpolator delay test
The test was passing real_delay=0 and relying on _check_delays to
silently override it with the index-based diff. Now passes real_delay=3
to match the 3 actions consumed during the simulated inference period.
* fix pr feedback
* ordering
* update hil script
* fix
* default name
* fix(bi_openarm): use kw_only=True to fix dataclass field ordering
BiOpenArmFollowerConfig overrides `id` with a default, making it
positional in the child — non-default `left_arm_config` then follows a
default field, which Python dataclasses forbid. Adding kw_only=True
(matching the parent RobotConfig) removes positional constraints.
Made-with: Cursor
* style: format long line in hil_data_collection.py
Made-with: Cursor
* pr feedback
---------
Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
* docs(toctree): add Benchmarks section for LIBERO and Meta-World
Move LIBERO and Meta-World pages out of the Simulation section into a
dedicated Benchmarks section so benchmark-specific docs are easier to
find and the Simulation section stays focused on environment hubs.
Made-with: Cursor
* docs(toctree): move IsaacLab Arena into Benchmarks section
Include NVIDIA IsaacLab Arena Environments alongside LIBERO and
Meta-World in the Benchmarks section.
Made-with: Cursor
* Add option for pi family models to train with relative actions (relative to state)
* formatting
* add recomputation of stats and option to compute delta stats
* normalzie after delta conversion
* only recompute state for stats
* calulate chunk based stats
* sample 100k
* load from parquet
* sample 1m
* stats per chunck
* fix
* use quantiles
* stats for entire dataset
* fix
* max 1m frames
* compute before dist
* fix multi gpu processor bug
* Fix RTC with delta actions and OpenArms motor_type wiring
* feat: align pi0_fast delta actions with pi0/pi05 and add RTC integration tests
- Add delta_exclude_joints and action_feature_names to PI0FastConfig
- Move to_absolute_actions from modeling to processor pipeline for pi0_fast
- Add delta action detection and logging to eval_with_real_robot.py
- Add delta actions documentation to pi0 and pi05 READMEs
- Fix ruff lint issues in test_delta_actions.py
- Add test_rtc_delta_actions.py (24 tests) covering:
- ActionQueue with delta vs absolute actions
- RTC denoise step with delta leftovers
- Full pipeline roundtrip (delta → RTC → absolute)
- State rebasing approximation bounds
- Non-delta policy compatibility
- Multi-chunk consistency
* chore: clean up test comments, add OpenPI attribution, remove debug logging
- Replace decorative comment separators in test files with plain section headers
- Add attribution comments for 1e-6 epsilon in normalize_processor.py (from OpenPI)
- Remove debug logging blocks from lerobot_train.py
* refactor: extract compute_delta_action_stats into compute_stats.py
Move the ~70-line inline delta action stats block from lerobot_train.py
into a dedicated function in compute_stats.py, where all other stats
computation already lives. The training script now calls it in 6 lines.
* refactor: remove unused get_processed_left_over from ActionQueue
This method was never called outside of tests. Leftover actions for RTC
guidance are always retrieved via get_left_over() (delta/original space).
* revert: remove logging-only changes from eval_with_real_robot.py
The delta actions detection helper and log message added no functional
value — the script already handles delta policies correctly via the
processor pipeline.
* refactor: use ACTION/OBS_STATE constants instead of hardcoded strings
Replace hardcoded "action" and "observation.state" with ACTION and
OBS_STATE from utils.constants in compute_stats.py, dataset_tools.py,
and lerobot_train.py.
* style: remove stray blank lines in training loop
* refactor: move delta action stats to preprocessing step, remove on-the-fly computation
- Remove on-the-fly compute_delta_action_stats from lerobot_train.py
- Rewrite recompute_stats to delegate action stats to compute_delta_action_stats
(chunk-based sampling matching what the model sees during training)
- Add chunk_size parameter to recompute_stats for delta action computation
- Add delta actions documentation to pi0.mdx and pi05.mdx
* feat: add recompute_stats CLI operation to lerobot-edit-dataset
* fix(tests): relax quantile normalization test tolerance for 1e-6 epsilon
* chore: remove agents_memory/pr_details.md from repo
* refactor: rename delta actions to relative actions throughout
What OpenPI calls "DeltaActions" is actually UMI's "relative trajectory"
representation: each action in the chunk is an offset from the current
state, not from the previous action. This avoids error accumulation.
Renamed across all source, tests, docs, and CLI:
- DeltaActionsProcessorStep → RelativeActionsProcessorStep
- to_delta_actions → to_relative_actions
- use_delta_actions → use_relative_actions
- delta_exclude_joints → relative_exclude_joints
- compute_delta_action_stats → compute_relative_action_stats
- delta_action_processor.py → relative_action_processor.py
- test_delta_actions.py → test_relative_actions.py
Kept as-is: AbsoluteActionsProcessorStep (converts TO absolute),
registry ID "delta_actions_processor" (backward compat), and unrelated
delta references (IK pipeline, Robosuite, RA-BC metrics, gym envs).
* docs: add Action Representations guide
Dedicated page explaining absolute, relative, and delta actions with
numerical examples, joint vs EE space, and how to use kinematics
pipelines and the relative action processor. References UMI paper
(Chi et al., 2024) for the terminology.
* docs: remove redundant OpenPI naming note from action representations
* docs: remove opinionated OpenPI reference from delta actions section
* docs: replace ASCII diagram with UMI paper figure
* docs: remove OpenPI reference from action representations
* docs: use HF-hosted image instead of local asset
* docs: clarify figure attribution
* revert: restore original normalization epsilon behavior
The 1e-6 unconditional epsilon change perturbed all normalized values,
breaking backward compatibility tests. The original approach (1e-8 eps
for MEAN_STD, conditional torch.where for QUANTILES) already handles
division by zero correctly without affecting non-degenerate cases.
* fix: restore delta_action_processor.py used by phone/RL teleop
The rename commit incorrectly deleted delta_action_processor.py and
duplicated its classes into relative_action_processor.py. Restore the
original file and import from it instead.
* fix(processor): address PR #2970 review comments
- Remove shebang from relative_action_processor.py (library module, not script)
- Add device alignment in to_relative_actions/to_absolute_actions so _last_state
on CPU doesn't cause cross-device errors when actions are on CUDA
- Rename delta_step → relative_step in AbsoluteActionsProcessorStep for naming
consistency; update factory.py, all processor files, and tests
- Expand _reconnect_relative_absolute_steps docstring to explain why post-hoc
rewiring is needed after deserialization
- Fix off-by-one in compute_stats.py: sample_upper_bound = total_frames - chunk_size + 1
so last valid start index is included and total_frames == chunk_size is not rejected
- Remove redundant NOTE comment in processor_pi05.py (duplicated two lines below)
- Fix pi0_fast processor ordering: move relative_step before NormalizerProcessorStep
so normalizer sees delta actions (matching pi0/pi05); flip postprocessor to
unnormalize → absolute accordingly. Relative stats are now required for all pi models
- Revert use_relative_joint_actions_aloha → use_delta_joint_actions_aloha in
configuration_smolvla.py (preserve existing public API)
- Update action_representations.mdx: add missing joint to 6-DOF example, fix
'based on a figure', clarify pi family ordering, add RTC compatibility section
* update rtc link
* feat: compute relative action stats over full dataset with optional parallelism
Remove the 100k sample cap from compute_relative_action_stats and process
all valid chunks. Vectorize with numpy (pre-load actions/states, fancy
indexing + broadcasting) for a large speedup over the per-index HF dataset
loop. Add num_workers param for thread-based parallelism (numpy releases
the GIL). Update docs to show --push_to_hub for recompute_stats.
* style: apply ruff formatting to compute_stats.py
* testing on real robot
* style: fix ruff format and remove redundant .keys() calls
* Fix SO-101 assembly instruction order to match videos
Motor horn installation steps were listed after placing motors
into the housing, but the assembly videos show installing horns
first. Reordered steps to match the videos, which is also the
easier approach since horns are harder to attach once the motor
is seated. Added missing detail that bottom horns don't require
screws.
* Update docs/source/so101.mdx
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Signed-off-by: Jai Kumaar Ratadia <jaikumaarratadia@gmail.com>
---------
Signed-off-by: Jai Kumaar Ratadia <jaikumaarratadia@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
* Add multitask diffusion transformer policy
Add multitask diffusion transformer policy
* expand the observation encoder to support differnt size encoders for vision and text
* add RoPE attention module as this is shown to help training dynamics and generation quality for DiTs
* update readme and citations for multitask dit policy
* remove dino vision encoder and simplify text and vision encoders by removing inheritance structure
* adjust factory comment
* update docstring for multitask dit policy processor file
* simplify config for multitask dit by merging and flattening everything, then adding comments to denote where some parameters are only used for specific objectives
* add references to the modeling file comments
* merge all modules files into the main modeling file
* add torch.no_grad decorators
* split up select action return statement
* remove redundant asserts
* add tutorial to training with multi_task_dit
* fix bugs when testing on hardware
* remove environment state conditioning
* update typo in test instruction comment
* add processor tests to multitask dit tests
* move policy to top of file
* use constants for indexing into batches and remove env state references
* remove the base classes since we don't need to be able to extend
* fix nit formatting in generate actions fcn
* reformat and clean up tutorial for multitask dit policy
* add more descriptions and depth to multitask dit tutorial
* note origins of each training objective
* rename config param for multiple vision encoders
* refactor code to perform task tokenization in the processor instead of in the modeling code for multitask dit
* add multitask dit to toc for docs
* add conditional transformers import to match all other policies that use transformers lib
* add test handling for multitask dit when transformers isnt available
* skip tests without transformers
* remove cropping of images smaller than the crop size
* add kwargs arg to multitask dit constructor
* add wallx dep conflict management for multitask dit policy
* use hyphens for cleanliness in pyproject.toml
* add conflict management to pyproject toml for pi conflict for mtdp as well
* update tests script to not use unnecessary uv sync call which resolves dependencies that do not need to run. This drastically reduces CI run time
* revert fast tests edits
* update docs and readme files, fixing some typos and adding multitask dit to readme
* chore(dependencies): upgrade transformers + hggingface-hub + peft + scipy
* chore(dependencies): bump pi0 family to transformers v5
* chore(dependencies): bump wall x to transformers v5
* chore(dependencies): bump gr00t to transformers v5
* chore(style): fix pre-commit
* fix(policy): xvla forced_bos_token missing
* test(rl): skip ci tests for resnet10
* Fix: full pi models support for transformer v5 (#2967)
* fix(pi): remove loss truncation
* fix(pi): remove state padding before tokenization
* fix(pi): fix image padding value
* fix from_pretrain
* add transformer v5 changes
* remove reference
* more fixes
* make it work
* add support for rest of pi family
* add pifast work
* more changes
* more changes
* more cleanup
* fix torch params
* dtype fix
* torch compile
* embed mismatch fix
* revert groot
* more nit fixes
* remove unused classes
* more fixes
* revert
* nit
* torch dtype warning fix
* but back dynamic renaming
* add tie embedding
---------
Co-authored-by: Yufei Sun <skieyfly@gmail.com>
* chore: fix XVLA in transformers v5 (#3006)
* test(policies): enable wall x CI testing
* style(test): pre-commit check
* style(test): pre-commit
---------
Signed-off-by: Bryson Jones <63133702+brysonjones@users.noreply.github.com>
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Jade Choghari <chogharijade@gmail.com>
Co-authored-by: Yufei Sun <skieyfly@gmail.com>
Co-authored-by: Steven Palma <steven.palma@huggingface.co>
* chore(docs): add more guidance to bring your own policies tutorial
* removing normalization to avoid confusion with processors
* trailing whitespace
* Update docs/source/bring_your_own_policies.mdx
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Signed-off-by: Maxime Ellerbach <maxime@ellerbach.net>
* Update docs/source/bring_your_own_policies.mdx
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Signed-off-by: Maxime Ellerbach <maxime@ellerbach.net>
* adding get optim params and predict_action chunk
* removing extra quotes
---------
Signed-off-by: Maxime Ellerbach <maxime@ellerbach.net>
* refactor(dataset): split reader and writer
* chore(dataset): remove proxys
* refactor(dataset): better reader & writer encapsulation
* refactor(datasets): clean API + reduce leaky implementations
* refactor(dataset): API cleaning for writer, reader and meta
* refactor(dataset): expose writer & reader + other minor improvements
* refactor(dataset): improve teardown routine
* refactor(dataset): add hf_dataset property at the facade level
* chore(dataset): add init for datasset module
* docs(dataset): add docstrings for public API of the dataset classes
* tests(dataset): add tests for new classes
* fix(dataset): remove circular dependecy
* add blog/guide
* add to tree
* chore(docs): rephrase rename_map docs for clarity and simplicity
---------
Co-authored-by: Steven Palma <steven.palma@huggingface.co>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
* docs(earthrover): update EarthRover Mini Plus dataset features and descriptions
* refactor(teleop): rename rover action keys to linear_velocity/angular_velocity
* fix(earthrover): align observation and action features with frodobots/berkeley-frodobots-lerobot-7k
* chore: address PR review comments
* ci: retrigger checks
* Add New featrue to lerobot_edit_datset.py that show dataset information.
* Fix to draccus error when happen give only --operation.type=info
* Updating test and documents regarding lerobot-edit-dataset info function.
* Updating documents regarding lerobot-edit-dataset extract function. option name in document is mistake.
* feat(datasets): Update to align formatting with pre-commit.(#2917)
Update to align formatting by pre-commit.
---------
Co-authored-by: Caroline Pascal <caroline8.pascal@gmail.com>
* docs: clarify installation steps are sequential, not optional
Add intro paragraph noting conda is one path (not the only one) and
number the three sections as steps so readers understand miniforge and
environment setup are prerequisites, not independent choices.
* Update installation guide link for LeRobot
Signed-off-by: Jai Kumaar Ratadia <jaikumaarratadia@gmail.com>
* Fix link formatting in installation guide again
Signed-off-by: Jai Kumaar Ratadia <jaikumaarratadia@gmail.com>
---------
Signed-off-by: Jai Kumaar Ratadia <jaikumaarratadia@gmail.com>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
* fix(motors): cleanup imports + fix signatures
* feat(motors): add damiao canbus + multiple fixes
* fix(motors): address comments -> last_state + different gains + sleep
* refactor(motors): reduce duplicated code + adressed some comments in the PR
* chore(motors): better timeouts
* tests(motors): damiao test and imports
* chore(deps): fix space
* feat(robot): add openarm leader
Co-authored-by: Pepijn <pepijn@huggingface.co>
* feat(robot): add openarm follower
Co-authored-by: Pepijn <pepijn@huggingface.co>
* refactor(robot): remove mechanical compensations and double arm assumption + rename
* chore(robots): remove left arm references
* refactor(teleop): multiple improvements to leader
* refactor(teleop): multiple improvements to leader
* feat(robots): add open arm to util CLI
* chore(robot): add alias openarm
* Apply suggestions from code review
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
* chore(motors): remove normalization tables damiao
* fix(motors): imports and signatures
* feat(motors): add motor_type_str + recv_id to motor class and _get_motor_recv_id raises if no motor_obj.recv_id
* chore(motors): remove normalize from base motor class and damaio
* tests(motors): remove bad tests (to be replaced)
* chore(motors): updated import check
* fix(robots): open arm mirrored config for joint limits
* chore(motors): update position_kd gain values
* chore(robots): set to 0 if openarm is calibrated at connect time
* chore(robots): remove macos in open arm as can doesn't support it
* chore(robots): update for motor_type_str in Motor class
* chore(robots): no default value for can port in open arms
* feat(robots): add bi manual openarm follower and leader
* use constant for kp and kd range and check responses in mit_control_batch()
* Add docs on setting up canbus and use damiao otor bus, also add lerobot_setup_can.py and log if there is not response from a write command
* precommit format
* supress bandit as these are intentional cli commands
* fix setup-can
* add test
* skip test in ci
* nit precommit
* update doc example
* dont import can for tests
* remove comment
* Add openarms docs
* format
* update purchase link
* can to none if nit availabl;e
* add canfd option in bus
* make handshake logic similar to lerobot-can
* type hint
* type check
* add temp teleop test
* remove script
* mock class
* mock class
* ignore linter
* pre-commit
* Add command for bimanual openarm
* fix import
* fix import leader
* fix import draccus
---------
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Pepijn <pepijn@huggingface.co>
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
* fix(motors): cleanup imports + fix signatures
* feat(motors): add damiao canbus + multiple fixes
* fix(motors): address comments -> last_state + different gains + sleep
* refactor(motors): reduce duplicated code + adressed some comments in the PR
* chore(motors): better timeouts
* tests(motors): damiao test and imports
* chore(deps): fix space
* feat(robot): add openarm leader
Co-authored-by: Pepijn <pepijn@huggingface.co>
* feat(robot): add openarm follower
Co-authored-by: Pepijn <pepijn@huggingface.co>
* refactor(robot): remove mechanical compensations and double arm assumption + rename
* chore(robots): remove left arm references
* refactor(teleop): multiple improvements to leader
* refactor(teleop): multiple improvements to leader
* feat(robots): add open arm to util CLI
* chore(robot): add alias openarm
* Apply suggestions from code review
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
* chore(motors): remove normalization tables damiao
* fix(motors): imports and signatures
* feat(motors): add motor_type_str + recv_id to motor class and _get_motor_recv_id raises if no motor_obj.recv_id
* chore(motors): remove normalize from base motor class and damaio
* tests(motors): remove bad tests (to be replaced)
* chore(motors): updated import check
* fix(robots): open arm mirrored config for joint limits
* chore(motors): update position_kd gain values
* chore(robots): set to 0 if openarm is calibrated at connect time
* chore(robots): remove macos in open arm as can doesn't support it
* chore(robots): update for motor_type_str in Motor class
* chore(robots): no default value for can port in open arms
* use constant for kp and kd range and check responses in mit_control_batch()
* Add docs on setting up canbus and use damiao otor bus, also add lerobot_setup_can.py and log if there is not response from a write command
* precommit format
* supress bandit as these are intentional cli commands
* fix setup-can
* add test
* skip test in ci
* nit precommit
* update doc example
* dont import can for tests
* remove comment
* Add openarms docs
* format
* update purchase link
* can to none if nit availabl;e
* add canfd option in bus
* make handshake logic similar to lerobot-can
* type hint
* type check
* add temp teleop test
* remove script
* mock class
* ignore linter
---------
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Pepijn <pepijn@huggingface.co>
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
* fix(motors): cleanup imports + fix signatures
* feat(motors): add damiao canbus + multiple fixes
* fix(motors): address comments -> last_state + different gains + sleep
* refactor(motors): reduce duplicated code + adressed some comments in the PR
* chore(motors): better timeouts
* tests(motors): damiao test and imports
* chore(deps): fix space
* Apply suggestions from code review
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
* chore(motors): remove normalization tables damiao
* fix(motors): imports and signatures
* feat(motors): add motor_type_str + recv_id to motor class and _get_motor_recv_id raises if no motor_obj.recv_id
* chore(motors): remove normalize from base motor class and damaio
* tests(motors): remove bad tests (to be replaced)
* chore(motors): updated import check
* use constant for kp and kd range and check responses in mit_control_batch()
* Add docs on setting up canbus and use damiao otor bus, also add lerobot_setup_can.py and log if there is not response from a write command
* precommit format
* supress bandit as these are intentional cli commands
* fix setup-can
* add test
* skip test in ci
* nit precommit
* update doc example
* dont import can for tests
---------
Signed-off-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Co-authored-by: Pepijn <pepijn@huggingface.co>
* feat(async_inference): server always sends CPU tensors, client handles device conversion
* fix:fix the type annotation of RawObservation in src/lerobot/async_inference/helpers.py
* update the import of robot_client
---------
Co-authored-by: Sato shinji <wwwsatoshinji@gmail.com>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
Co-authored-by: KB <kevin-brian.n-diaye@epita.fr>
* improve image2video
* add episodes video encoding
* fix mypy failing
* iterate on review
* nit
* remove max, and let it be optional
* iterate more
* update docs
* fix test
---------
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
This PR extends the integration of Unitree g1 with the LeRobot codebase. By converting robot state to a flat dict we can now record and replay episodes (example groot/holosoma scripts need to be adjusted as well). We also improve the simulation integration by calling .step @ _subscribe_motor_state instead of it running in a separate thread. We also add ZMQ camera to lerobot, streaming base64 images over json
* feat(robots): consolidates bi SO setups
* fix(robots): solve circular dependecy
* fix(robots): teleop & record working
* feat(robots): only one SO
* fix(utils): rename bi so
* fix(scripts): bi so import
* fix(rl): remove imports
Pepijn