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name: robotics-control description: "Use Newton robotics APIs for actuators, controllers, inverse kinematics, selection views, sites, robot target layouts, and optional neural policies." disable-model-invocation: true metadata: disco-role: operating repo: newton sub-skill-id: robotics-control license: Apache 2.0

Newton robotics-control

Use this sub-skill when the task involves Newton robot actuation, joint controllers, inverse kinematics, batched articulation selection, robot sites, or policy-controller dependency checks.

Route here for

• newton.actuators: Actuator, ControllerPD, ControllerPID, clamping stages, Delay, and neural actuator checkpoint notes.
• newton.controllers: ControllerJointImpedance and ControllerJointImpedanceModelFree workflows.
• newton.ik: IKSolver, position/rotation/joint-limit objectives, seed sampling, and target updates.
• newton.selection.ArticulationView: label-pattern selection, replicated-world views, DOF/link/root getters and setters, and actuator-parameter access.
• Robot target-control migration, especially newton.use_coord_layout_targets and Model.joint_target_q_start.
• ModelBuilder.add_site() and shape methods with as_site=True when sites are used as robot markers, end-effector frames, or control/sensor attachment points.
• Optional ONNX/Warp-NN and Torch policy dependency diagnostics without downloading assets.

Route elsewhere

• Sensor update timing, camera/IMU/contact sensor allocation, and viewer output: use the sensors/visualization route.
• URDF, MJCF, USD parsing flags and asset resolver behavior: use the asset import/export route.
• Solver choice, contact tuning, MuJoCo/XPBD/Kamino tuning, and contact-buffer sizing: use the solvers/contacts route.
• Core model-building loops, shapes, joints, and collision setup not specific to robotics control: use the modeling/simulation route.

Bundled references

• references/actuators-controllers-ik.md — public robotics API surfaces, target arrays, controllers, and IK contracts.
• references/robotics-recipes.md — migration and debugging recipes for coordinate-layout targets, replicated-world selection, sites, IK, and policies.
• references/troubleshooting.md — common robotics-control failure modes and fixes.

Bundled diagnostic

Run the safe API diagnostic from any working directory:

python path/to/sub-skills/robotics-control/scripts/check_robotics_apis.py

The script imports only public Newton modules, prints relevant signatures when available, and checks optional ONNX/Warp-NN/Torch policy dependencies by import availability only. It performs no downloads and does not run simulations.

Operating rules

• Import through public modules only: newton, newton.actuators, newton.controllers, newton.ik, and newton.selection.
• Set newton.use_coord_layout_targets = True once, before constructing any ModelBuilder, for new robot code that writes position targets.
• Use Control.joint_target_q for joint positions, Control.joint_target_qd for joint velocities, Control.joint_act for feedforward actuator input, and Control.joint_f for generalized effort.
• When selecting by labels, remember that ordinary strings are glob patterns; compile a re.Pattern for regular-expression full matching.
• Keep optional policy workflows explicit: ONNX checkpoints need the ONNX/Warp-NN stack; Torch .pt, .pth, or .pt2 policies need PyTorch.