cuRobo: CUDA Accelerated Robot Library

[API] [GTC Talk] [Code] [Paper]

cuRobo is a CUDA-accelerated library for robot motion generation, built on PyTorch, CUDA, and Warp. It provides GPU-parallel algorithms for forward/inverse kinematics, collision checking, trajectory optimization, geometric planning, GPU-native perception, and whole-body motion generation, scaling from single-arm manipulators to high-DoF humanoids.

cuRobo performs collision-free pick-and-drop motions on YAM using stereo-camera perception.
cuRobo integrates depth from a depth camera into a TSDF map, generates ESDF, and enables collision-free motions.
cuRobo generating collision-free motions on a NVIDIA Jetson ORIN.
Whole-body policy trained in MimicKit (Newton) using retargeted motions from cuRoboV2.

Updates

  • November 4, 2026 (v0.9.0): cuRoboV2-Fast, Cartesian waypoint planning, GPU bidirectional RRT, torque-limited TimeOpt, C++ deployment, and robot pose calibration. With a 3 kg payload, cuRoboV2-Fast achieves 4.4 ms mean planning time on RTX 5090, 14.7× faster than cuRoboV2. A stereo-camera-based YAM deployment achieves 5.93 s mean completed pick-and-drop cycles, 34.6% shorter than cuRoboV2. See Technical Reports for details.

  • July 9, 2026: Add visibility-tested textured mapper outputs, independent RGB and neural-feature resolutions, and faster TSDF mesh extraction for real-time visualization.

  • June 15, 2026: Add LiDAR TSDF, RGB, and feature fusion, compact mapper block checkpointing, and live RealSense RGB-D mapping with MPC.

  • April 27, 2026: Add feature channel integration in TSDF mapper, improve TSDF mapper performance (1.5ms to 0.5ms).

  • April 2026 (v0.8.0): cuRoboV2, complete rewrite of cuRobo with new features and improvements.

  • 2024 (v0.7.x): Sub-millimetre IK precision, mimic joints, ESDF voxel collision checker, Grasp API planning, trajectory re-timing.

  • Oct 2023 (v0.6.0): Initial release with Technical Report.

See CHANGELOG for details.

Documentation

  • Getting Started: Step-by-step tutorials covering installation, robot setup, kinematics, IK, MPC, motion planning, and volumetric mapping.

  • Guides: Writing custom optimization problems, cost terms, and optimizers.

  • Reference: API, style guide, runtime configuration, benchmarks, sphere fitting, and self-collision.

Research

Read the cuRobo technical reports for algorithm details and benchmarks.

Technical Reports