chungmin99/pyroki

Health v2 · maintenance only

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1682 stars · 183 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PyRoki is a modular Python toolkit for robot kinematic optimization built on JAX, providing differentiable forward kinematics from URDFs, collision primitives, and composable costs. It unifies inverse kinematics, trajectory optimization, and motion retargeting via a Levenberg-Marquardt solver with manifold optimization and hard constraints, running on CPU, GPU, and TPU.

Use cases

• solve inverse kinematics for a robot arm from a URDF
• optimize robot trajectories with collision avoidance
• retarget human hand or body motion to robot hands and humanoids
• compute differentiable forward kinematics in a JAX pipeline
• optimize end-effector pose and manipulability objectives
• generate collision capsules from robot meshes automatically

When to choose

• you need differentiable or batched kinematics and IK in Python with GPU/TPU support
• you want composable costs for IK, trajectory optimization, or motion retargeting in one framework
• your robot uses revolute, continuous, prismatic, or fixed joints in a kinematic tree

When to avoid

• you need sampling-based motion planning with graphs or trees
• you require closed-loop kinematic chains or parallel manipulators
• you need fast mesh-level collision checking in collision-heavy scenarios

Facets

library · maturity active

simulation math machine-learning robotics gpu-computing python cross-platform robot-kinematics inverse-kinematics jax urdf trajectory-optimization motion-retargeting collision-avoidance differentiable-programming algorithms gpu

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