Note: This project is in early development. The API may change between releases, so pin a version before depending on it.
Inspect Robots has two swappable inputs: a Policy (the VLA brain) and an
Embodiment (the robot body + world). This package provides both for the
YAM + MolmoAct2 stack, so any embodiment-agnostic Inspect Robots task (e.g. all of
KitchenBench) runs on real arms:
molmoact2policy: a thin client for MolmoAct2's first-party bimanual-YAM/actserver (the model owns the GPU + weights in its own process).yam_armsembodiment: the I2RT driver with joint-position control by default and an opt-in Cartesian end-effector interface, plus a hard safety clamp, operator-in-the-loop success, and self-paced control.
Both declare the same 14-D joint-position contract (2 arms × [6 joints +
gripper], cameras top/left/right, packed joint_pos state), so Inspect Robots's
compatibility check passes with zero errors and zero warnings. This is
verifiable before any motion.
inspect-robots run --task kitchenbench/pour_pasta --policy molmoact2 --embodiment yam_arms
Note: cameras are configured with three plain device paths (
top/left/right_cam_device), so the whole rig is drivable from config.ini or-E key=valueflags with no custom code. A Pythoncamera_readerremains available for exotic camera stacks. With neither configured,yam_armsfails fast with aConfigErroratreset(), before any driver connect or motion.
The builtin reader drains each camera continuously on its own thread, so an
observation carries a frame about one camera frame interval old: 33 ms at
30 fps. Without that, a V4L2 queue read at control_hz hands back a frame
N/control_hz old, measured at 380 ms on a 10 Hz rig and worse as the control
rate falls. Two limits worth knowing: freshness is bounded by the camera's own
frame rate, which no setting here changes (a 5 fps camera means 200 ms whatever
the control rate), and a camera that stops delivering for half a second raises
rather than serving a stale frame. A custom camera_reader that owns devices
should expose a close(), which the embodiment calls during teardown.
Install (on the robot/GPU machine)
uv venv && source .venv/bin/activate
uv pip install inspect-robots-yam
# The i2rt driver is git-only and not on PyPI. Install it directly.
# The build-constraints file works around a build failure in i2rt's ruckig
# dependency (source-only releases that no longer build under scikit-build-core
# 1.0; the pin below 0.10 matches i2rt's own in-repo workaround):
echo 'scikit-build-core<0.10' > build-constraints.txt
uv pip install --build-constraints build-constraints.txt "i2rt @ git+https://github.com/i2rt-robotics/i2rt@db582eaa70b6a057a1e2981da6219dfa6c29422a"
The base package includes the /act transport and builtin OpenCV camera reader.
Only i2rt, the I2RT YAM arm driver required for real hardware, needs the
separate git install. The scikit-build-core build constraint can be dropped
once ruckig ships a release with the fix from
pantor/ruckig#261 and i2rt
moves off ruckig==0.15.3. The camera reader depends on
opencv-python-headless; if your environment also carries opencv-python,
the two share the cv2 module and the last one installed wins.
Then download the model weights (needs a Hugging Face token) and start the server, from the MolmoAct2 repo:
huggingface-cli download allenai/MolmoAct2-BimanualYAM
python examples/yam/host_server_yam.py # serves /act on :8202
Serving a GR00T fine-tune
Run the shim from an Isaac-GR00T
environment with a CUDA, PyTorch, and flash-attn stack that supports the GPU.
Blackwell GPUs (sm_120) require a matching PyTorch build. Download the YAM
fine-tune and start its /act server on the default port 8203:
hf download robocurve/gr00t-n1.7-yam-molmoact2
python scripts/serve_gr00t_act.py \
--model robocurve/gr00t-n1.7-yam-molmoact2
Then run it through the distinct gr00t policy entry point so eval logs carry
the correct model family:
inspect-robots "stack the red block on the blue block" \
--policy gr00t --embodiment yam_arms
The client defaults to http://127.0.0.1:8203. Override a remote or alternate
server with -P server_url=http://gpu:8203. The config key is server_url;
url is a read-only property, and ActServerConfig.from_kwargs rejects it.
For another GR00T fine-tune, pass -P action_horizon=<its chunk length> so the
recorded policy metadata matches that checkpoint.
Warning: The shim's startup checks validate the packed layout and units ranges, but joint polarity and absolute-vs-delta semantics cannot be detected from dataset statistics. For the first runs with a new checkpoint family, run
inspect-robots-yam-preflight, leave guardrails on, and keep an operator at the e-stop.
Preflight: prove compatibility before any motion
Check dims, semantics, cameras, and state keys:
inspect-robots-yam-preflight
Also check a specific task's scenes are realizable:
inspect-robots-yam-preflight --task kitchenbench/pour_pasta
Affirm that no motion will occur:
inspect-robots-yam-preflight --dry-run
A green preflight means action dim (14), control mode (joint_pos), cameras, and
state keys all line up. It does not prove the joint values are interpreted the
same way. See Safety below.
Run on hardware
Write your defaults once. The interactive wizard interviews this plugin's declared devices (three cameras and both arms' CAN channels) with live probes, including unplug-to-identify:
inspect-robots setup
Or write the file yourself, replacing the three camera paths with your rig's
V4L2 color nodes (use stable /dev/v4l/by-id/... or udev-symlink paths;
bare /dev/videoN numbers reshuffle on every replug):
mkdir -p ~/.config/inspect-robots && cat > ~/.config/inspect-robots/config.ini <<'EOF'
[defaults]
policy = molmoact2
embodiment = yam_arms
scorer = success_at_end # scores the operator's y/N answer at episode end
max_steps = 1200 # 120 s at 10 Hz
rerun = true # live viewer of cams/state/actions (inspect-robots[rerun])
store_frames = true # keep the policy's camera frames per run
[embodiment.args]
top_cam_device = /dev/v4l/by-id/YOUR-TOP-CAM
left_cam_device = /dev/v4l/by-id/YOUR-LEFT-CAM
right_cam_device = /dev/v4l/by-id/YOUR-RIGHT-CAM
EOF
Make sure the plugin is installed and the MolmoAct2 server is up. The
molmoact2 policy is only a client: nothing moves until the server is
listening, and it does not start itself or survive a reboot (full setup in
Install):
uv pip install inspect-robots-yam # provides the molmoact2 policy + yam_arms rig
# On the GPU machine, from the MolmoAct2 repo. Leave it running, e.g. in tmux:
python examples/yam/host_server_yam.py --host 0.0.0.0 --port 8202
curl http://127.0.0.1:8202/act # 200 means the server is ready
Then tell the robot what to do:
inspect-robots "place the fork on the plate"
The attended flow: position the scene, press Enter to start, press any key to
end the episode, answer y/N to score. The status line counts up against the
run's real step limit (t = 42s / 120s) with no configuration needed
(requires inspect-robots newer than 0.8.1; on older cores set
max_steps_hint).
For exotic camera stacks (or full programmatic control), the Python API takes
a custom camera_reader returning
{"top_cam", "left_cam", "right_cam": HxWx3 uint8}:
from inspect_robots import eval
from inspect_robots.approver import ClampApprover
from inspect_robots_yam import MolmoAct2Policy, YAMEmbodiment, YamConfig
emb = YAMEmbodiment(YamConfig(left_channel="can0", right_channel="can1"),
camera_reader=my_camera_reader)
pol = MolmoAct2Policy(server_url="http://127.0.0.1:8202")
(log,) = eval("kitchenbench/pour_pasta", pol, emb,
approver=ClampApprover(emb.info.action_space)) # defense in depth
print(log.status, log.results.metrics)
At each episode end the embodiment asks the operator (y/N); a yes records
termination_reason="success", which KitchenBench's task_success scorer reads.
The operator prompts need an interactive terminal: a dead stdin raises
EmbodimentFault (the framework's always-halt path). For runs with no operator,
set YamConfig(unattended=True) (CLI: -E unattended=true): all operator
prompts are skipped and every episode runs to max_steps, scoring as a failure.
Drive the arms with an LLM (agent mode)
With the inspect-robots-agent
plugin installed, a frontier LLM can drive the arms directly: it sees the
cameras and the labeled 14-D state, and moves joints by name
(left_j0..left_gripper, right_j0..right_gripper) through smooth,
approver-checked motions.
Put a .env with your API key in the working directory, reusing one you already have or copying the .env.example template (the CLI loads it automatically; real environment variables take precedence over its values):
ANTHROPIC_API_KEY=sk-ant-...
Install the add-on:
uv pip install inspect-robots-agent inspect-robots-yam
inspect-robots config set embodiment yam_arms # once, per machine
Cameras come from the builtin reader: set the three *_cam_device paths in
~/.config/inspect-robots/config.ini (see Run on hardware above) or pass them as
-E flags per run. Then run the LLM on the robot:
inspect-robots "place the fork on the plate" --policy agent \
-P model=anthropic/claude-fable-5
Note: Invoke the CLI as plain
inspect-robots, notuv run inspect-robots. Inside a uv project,uv runfirst re-syncs the environment to the project's lockfile, downgrading whatever theuv pip installcommands above just added back to the locked versions; the only trace is an easy-to-miss "Uninstalled N / Installed N packages" line. To useuv runanyway, pass--no-sync, or declare everything as real dependencies withuv add inspect-robots-yamplus your plugins.
Safety guardrails (a bounds clamp plus a per-step delta limit derived from the
declared action space) are wired in by default for every CLI run; turning them
off requires an explicit --disable-guardrails.
Cartesian EEF mode
For LLM-agent runs, opt into the 10-D absolute Cartesian interface:
[embodiment.args]
control_interface = eef_pos
Each arm is controlled as x, y, z, yaw, gripper. Positions are metres in
that arm's own base frame, with +x forward from the base and +z up. The two
base frames are independent. On common mirrored bimanual mounts, the arms'
+y axes point in opposite world directions, so equal signed y targets do not
mean equal world directions.
Yaw is an absolute target relative to the orientation captured at reset:
0 means the reset orientation. It rotates about base +z while preserving the
captured roll and pitch. Yaw interpolation does not wrap. A move from 3.1 to
-3.1 sweeps through zero instead of taking the short path, so use
intermediate yaw targets for near-±π regrasps.
The default workspace per arm is x [0.15, 0.48], y [-0.25, 0.25], and z
[0.03, 0.40], with yaw [-π, π] and gripper [0, 1]. These bounds were
validated against the bundled YAM + LINEAR_4310 model at the default working
orientation, but they are a conservative box rather than an exact reachable
set. eef_low and eef_high override all ten bounds. The observation keeps
the 14-D joint_pos field for logging and adds the command-aligned 10-D
eef_state field.
In both control interfaces, home_pose=None selects a mandatory per-mode
factory default instead of skipping homing. Joint mode uses the
dataset-verified DEFAULT_JOINT_HOME_POSE, with every joint at encoder zero
and both grippers open. EEF mode uses DEFAULT_EEF_HOME_POSE; its provisional
per-arm joints are [-0.024, 0.794, 0.645, -0.375, -0.021, -0.012], with both
grippers open. The first EEF reset validates that the configured home FK lies
in the workspace box before moving, then captures each arm's yaw reference
after homing.
Warning: EEF mode has no arm-table or arm-arm collision checking. The workspace box, Cartesian guardrails, joint-space IK rate limit, oscillation hold, and joint limits are the only geometric protections. The two default y ranges overlap. Keep an operator at the e-stop; using EEF mode unattended is operator discretion and requires rig-specific validation.
Warning: Before any unattended agent run, verify on your rig that the arms hold position while the LLM thinks (seconds between action chunks). Run the bundled check per arm and per mode, arms mid-workspace, e-stop in hand:
inspect-robots-yam-holdcheck can_left --zero-gravity true inspect-robots-yam-holdcheck can_right --zero-gravity true(Channel names match your rig's CAN interfaces;
can0/can1on default setups.) PASS in the mode you run agents in closes the verification. The defaultzero_gravity_mode=trueputs the i2rt driver in a gravity-compensated, compliant mode; if it drifts but--zero-gravity falseholds, run agents with-E zero_gravity_mode=false. If both drift, file an issue with the numbers. Keep a hand on the e-stop for the first runs.
YAM ships with a factory resting pose at encoder zero for every joint and 1.0 (open) for both grippers. It equals the joint-mode factory home, so standard upright rigs end with a gentle 3-second park and the next episode begins with open grippers. Override it per rig when needed. Pose fields accept comma-separated values from the CLI and config.ini. For example, a per-rig rest target can retain measured joint offsets while parking open:
[embodiment.args]
rest_pose = -0.002,0.002,0.002,-0.089,0.007,-0.026,1.0,-0.006,0.002,0.001,-0.087,-0.007,-0.019,1.0
Set rest_pose = none to opt out of the factory target and park at the pose
captured before the first commanded motion instead.
In delta mode (-E joints_are_delta=true) the declared action space is the
per-step displacement box (YamConfig.step_limits, default 0.2 rad per joint
and a full gripper stroke per step); the absolute joint limits still clamp the
summed command inside the embodiment as a backstop. A delta-configured rig
must be paired with a delta-declaring policy (-P joints_are_delta=true for
molmoact2); a mismatch fails the compatibility check before any motion.
Safety
-
Hard clamp backstop. Every command is clipped to
YamConfig.joint_low/highinsidestep(), independent of any Inspect RobotsApprover: unclamped model outputs can never reach the motors. Set the arm slots to your real YAM joint limits (the defaults are conservative placeholders: joints ±π, gripper 0–1). But note the limits are in policy units per the table below: gripper slots 6 and 13 stay normalized 0–1, only slots 0–5 and 7–12 are radians. -
Use
ClampApproveron hardware for a second layer. -
Zero-gravity handoff jump. The arms connect in zero-gravity mode by default (
YamConfig(zero_gravity_mode=True), passed through to the i2rt driver). Homing and rest-pose motions ramp atcontrol_hz, but the first policy action in joint mode is still a stiff PD command that can jump from wherever the arm ended up. Nothing bounds the per-step joint delta in absolute joint mode yet (tracked as a known issue). EEF mode applies a 0.2-rad-per-joint per-step IK backstop, but a six-joint branch transit can still move the EEF tens of centimetres because rate-clamped intermediate configurations are not IK solutions. Reset always moves the arms through the full homing ramp, and every mode has a factory home. Attended runs issue a stand-clear prompt before the first homing ramp of each connection. Stand clear when the episode starts, and usehome_poseas the per-rig override when the factory start is not validated for your setup. -
EEF reachability and collision limits. Iteration-cap non-convergence uses the solver's finite last iterate as best effort, and the next
eef_statereports the true result. IK branch flips are joint-rate-clamped and repeated reversals hold the whole affected arm temporarily. These controls do not check collisions or guarantee a Cartesian path during a clamped branch transit. Raised work surfaces also need a raised EEF z minimum: the defaultz_min=0.03leaves only about 19 mm nominal fingertip clearance over a table at the arm-base plane, less up to 5 mm of IK error. -
Park pose must rest under gravity. On close, the arms ramp back to an explicit per-rig
rest_poseor the factory zero-joint, open-gripper target, and torque is released once the ramp finishes. Setrest_pose=noneto opt out and fall back to the pose captured at the first reset. Verify that the factory target is a supported resting pose on your rig, or start runs (or setrest_pose) with the arms in one, not held mid-air: whatever pose the park ends in is the pose the arms go limp from. The park path is not collision-checked, so keep the workspace clear at episode end. The default parks with both grippers open (wire 1), so parking releases anything still held during the ramp, wherever the arms happen to be. Rigs that must keep an object gripped at park should overriderest_posewith gripper slots 0.0. Override bothhome_poseandrest_poseon rigs whose joint limits exclude zero, since both targets are clamped through the same per-joint box as every command. -
Absolute vs. delta joints: verify first. MolmoAct2's YAM
actionsare treated as absolute joint targets by default. If your checkpoint emits deltas, setYamConfig(joints_are_delta=True)(the embodiment converts to absolute internally so the declaredjoint_posstays honest). Inspect Robots's compat check cannot tell these apart: confirm with--dry-runand a single slow jog before running a task. -
Gripper polarity/trim. The wire convention is normalized 0–1, with 1 open and 0 closed. The defaults (
gripper_open=1.0,gripper_closed=0.0) preserve an identity map for the standard i2rt driver. These fields are the measured driver-native positions at the open and closed ends of the stroke. Configure an inverted or offset gripper with its actual endpoints, for examplegripper_open=0.72, gripper_closed=0.04. Commands are de-normalized on the way out and observations are re-normalized on the way back, so the model always sees the wire convention. Warning: values outside [0, 1] are forwarded on a path i2rt does not clip. Avoid them unless you have verified your firmware's behavior.Compatibility (pre-1.0): earlier releases interpreted these fields with the opposite endpoint mapping. A config that explicitly copied the old defaults (
gripper_open=0.0,gripper_closed=1.0) now inverts its gripper. A config that followed the old inversion recipe (gripper_open=1.0,gripper_closed=0.0) no longer inverts because those values are now the identity defaults. On identity-calibrated rigs,home_pose,rest_pose, and customjoint_low/joint_highretain their numeric behavior, but their gripper-slot meaning is now 1 open and 0 closed.
Configuration
Joint-space vectors
joint_low/joint_high, home_pose, rest_pose, actions, and the observed
joint_pos state all use policy units:
| Slots | Meaning | Unit |
|---|---|---|
| 0–5, 7–12 | left / right arm revolute joints | radians |
| 6, 13 | left / right gripper | normalized 0–1 (1 = open, 0 = closed) |
Hardware gripper units (via gripper_open/gripper_closed) exist only at the
driver boundary; pose and limit vectors never use driver-native gripper units.
In control_interface="eef_pos", actions and eef_low/eef_high are 10-D:
| Slots | Meaning | Unit |
|---|---|---|
| 0–2, 5–7 | left / right EEF x, y, z in each arm's base frame | metres |
| 3, 8 | left / right yaw relative to reset orientation | radians |
| 4, 9 | left / right gripper | normalized 0–1 (1 = open, 0 = closed) |
home_pose, rest_pose, joint limits, and parking remain 14-D joint-space
vectors in both control interfaces.
YamConfig: left_channel, right_channel, gripper_type (i2rt GripperType
enum name, e.g. LINEAR_4310; grippers only: NO_GRIPPER/YAM_TEACHING_HANDLE
would break the 14-D packing and are rejected), control_hz, cam_height/width,
joint_low/high, control_interface (joints by default or eef_pos),
docs_extra (rig-specific notes appended to the built-in agent documentation),
eef_low/high, ik_max_iters, ik_step_joint_limit,
cmd_resync_threshold, osc_deadband, osc_reversals, osc_window,
osc_hold_steps, home_pose (reset always ramps here smoothly over
rest_secs; none selects DEFAULT_JOINT_HOME_POSE in joint mode or
DEFAULT_EEF_HOME_POSE in EEF mode), rest_pose (close park target; defaults
to the factory zero-joint, open-gripper pose equal to the joint factory home,
accepts a per-rig override, and accepts none to fall back to the pose captured
at the first reset before torque is released),
rest_secs (ramp duration, default 3.0), gripper_open/closed,
joints_are_delta, zero_gravity_mode (default True; see Safety),
unattended (default False; skip operator prompts),
settle_tolerance (radians; none by default, which disables settling; see
Settling before observing), settle_timeout_s (default 1.0),
settle_timeout_budget (default 20),
top/left/right_cam_device (V4L2 paths for the builtin camera reader; all
three or none), max_steps_hint (deprecated: on inspect-robots newer than
0.8.1, framework runs feed the status line the real horizon automatically;
the hint is only a fallback for direct rollout() calls or older cores;
bounds nothing).
The current factory value is available for inspection as
inspect_robots_yam.config.DEFAULT_REST_POSE; this is an informational constant,
not a stable import.
ActServerConfig: server_url, endpoint, num_steps (the wire field: the
server's flow-matching denoising steps, not the chunk length),
action_horizon (the checkpoint's advertised chunk length, 30 for the bimanual
YAM tag; metadata only), timeout_s, camera_order, state_key,
cam_height/width, name (the policy label recorded in eval logs).
Scalar knobs are settable from the CLI:
inspect-robots run -P server_url=http://gpu:8202 -E left_channel=can0 ....
Settling before observing
By default step() commands a pose, paces out the control period, and observes,
without checking that the arm arrived. A VLA running closed loop at control_hz
is fine with that, since its next observation is 100 ms away either way.
Chunked policies are not. The agent policy interpolates one tool call into up
to 100 actions and only looks at the observation from the last of them, so it
plans its next motion from a pose the arm may not have reached.
Setting settle_tolerance makes step() and reset() wait for every arm joint
to come within that many radians of the commanded pose first:
inspect-robots "place the fork on the plate" --policy agent \
-P model=anthropic/claude-opus-5 \
-E settle_tolerance=0.05 -E zero_gravity_mode=false
Three things to know before turning it on.
Pick the tolerance from your rig, not from this example. Run
inspect-robots-yam-holdcheck and use a value comfortably above the settle
figure it reports. A tolerance at or below your rig's steady-state control offset
can never be met, so the first settle_timeout_budget steps each burn
settle_timeout_s before settling disables itself for that trial.
Take that figure in the mode you will run, and expect
zero_gravity_mode=false. Settling presumes a servo that holds position. The
default gravity-compensated mode is compliant and may drift instead of holding.
It guarantees the arm reached what was commanded, not what the policy asked
for. In eef_pos mode an oscillation hold, a failed IK solve, or the per-step
rate clamp all re-send the previous pose, and settling against that succeeds
immediately. Commands are also clamped to joint_low/high, which can sit outside
the reachable range.
Timeouts are not failures: the step observes anyway and records
settled/settle_residual/settle_timeouts in StepResult.info. After
settle_timeout_budget timeouts in a trial, settling switches off for the rest
of that trial, warns, and marks every later step with settle_disabled. A scorer
that judges the final state should check for it. Those per-step values reach
scorers and custom sinks; they are not written to the JSON eval log.
Note: Settling does not make the camera image postdate the motion. OpenCV can return a frame the V4L2 driver captured and queued earlier, so a settled arm can still be photographed mid-motion. See issue #63.
With settling on, the operator status line and its Max ...s horizon count steps
rather than wall-clock seconds, so both understate real elapsed time (#64).
Development
Dependency changes: after editing dependencies in
pyproject.toml, runuv lockand commit the updated lockfile. CI installs withuv sync --lockedand fails with "the lockfile needs to be updated" if you forget. Day-to-day conventions (PR-onlymain, the requiredci-okcheck, one-click releases) are documented inCLAUDE.md.
uv venv && uv pip install -e ".[dev]" # inspect_robots + kitchenbench from PyPI
uv run pre-commit install
uv run pytest --cov # 100% coverage required
uv run ruff check . && uv run mypy
Every public module, class, and function needs a docstring, enforced by Ruff D1; state the contract instead of restating the symbol name.
The whole suite runs with no hardware, no server, and no stdin: the i2rt
driver, cameras, the /act transport, the clock, and operator I/O are all
injected. The default hardware seams are excluded from coverage (# pragma: no cover).
Citation
If you use Inspect Robots YAM in your research, please cite it:
@software{inspect-robots-yam,
author = {Robocurve},
title = {Inspect Robots YAM: Adapters for I2RT YAM bimanual arms},
year = {2026},
url = {https://github.com/robocurve/inspect-robots-yam},
version = {0.3.0},
license = {MIT}
}
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| MD5 |
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Provenance
The following attestation bundles were made for inspect_robots_yam-0.14.0-py3-none-any.whl:
Publisher:
release.yml on robocurve/inspect-robots-yam
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
inspect_robots_yam-0.14.0-py3-none-any.whl -
Subject digest:
67cef81e7077f578cb58e4b386d8ff543a5baaf7b5c78ea5855755239349f110 - Sigstore transparency entry: 2238009530
- Sigstore integration time:
-
Permalink:
robocurve/inspect-robots-yam@dbf9efbf4cea2dd234e0b65bd53f1fde298a2e5b -
Branch / Tag:
refs/heads/main - Owner: https://github.com/robocurve
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release.yml@dbf9efbf4cea2dd234e0b65bd53f1fde298a2e5b -
Trigger Event:
workflow_dispatch
-
Statement type: