Use LiDAR to map the static world
- slam
- lidar
- lidar-point-cloud
- gps
77,353 visible repositories in the index
169–192 of 221 · Most stars
Use LiDAR to map the static world
Bayesian Generalized Kernel Inference for Terrain Traversability Mapping
RAX harness: coding agents that learn robot tasks by online exploration
A robust sensor fusion library for online localization.
[LIBERO-MAX] A paired benchmark for robot-policy robustness to controlled changes introduced during execution.
An Event-Driven, Asynchronous, Behavioral State Machine Library for ROS (Robotic Operating System) applications written in C++
TUM Roborace Team Software Stack - Path tracking control, velocity control, curvature control and state estimation.
SuperMimic-UniLab: An Independent reproduction of SuperMimic on UniLab for whole-body humanoid motion tracking.
Library for working with the AxiDraw v3 pen plotter.
Fiducial markers for SLAM.
Open source self-driving software for low speed environments
The first exam for code agents in the physical world: frozen robot tasks from many benchmark suites, each answered with a program and verified in a separate sandbox. Runs on Harbor.
Embodied In-Context Learning for GPT-6 Astra
The repository host gives no description.
The repository host gives no description.
RobotAgentBench: A benchmark for evaluating open-world robot autonomy in realistic household environments.
Artificial Intelligence for Kinematics, Dynamics, and Optimization
Whole-body motion tracking for the Unitree G1 in about 3 minutes on one GPU.
A high-performance, general-purpose toolkit for versatile robotic tasks.
RAFCON (RMC advanced flow control) uses hierarchical state machines, featuring concurrent state execution, to represent robot programs. It ships with a graphical user interface supporting the creation of state machines and contains IDE like debugging mechanisms. Alternatively, state machines can programmatically be generated using RAFCON's API.
The repository host gives no description.
The repository host gives no description.
Whole-body motion tracking for the Unitree G1 in under 3 minutes on average on one GPU: return 0.82 with 0/40 clips failed, held from 2.74 min (mean of 15 seeds, range 2.21-3.61, fine checkpoints), 11.87 it/s (world model + Muon + overlapped CUDA streams, mjlab)
Cross-platform clone of the FRC Driver Station