Venom
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Ground_based_autonomy_basic | 408 | 7 months ago | 4 | C++ | ||||||
| Autonomous Navigation and Collision Avoidance for Ground Robots | ||||||||||
| Traversability_estimation | 237 | 10 months ago | 7 | other | C++ | |||||
| Traversability mapping for mobile rough terrain navigation | ||||||||||
| Quadruped_ctrl | 184 | 2 years ago | 8 | mit | C++ | |||||
| MIT mini cheetah quadruped robot simulated in pybullet environment using ros. | ||||||||||
| Robogrammar | 175 | a year ago | 7 | mit | C++ | |||||
| RoboGrammar: Graph Grammar for Terrain-Optimized Robot Design (SIGGRAPH Asia 2020) | ||||||||||
| Venom | 146 | 3 years ago | mit | Python | ||||||
| All Terrain Autonomous Quadruped | ||||||||||
| Dstar Lite Pathplanner | 109 | 5 months ago | mit | Python | ||||||
| Implementation of the D* lite algorithm in Python for "Improved Fast Replanning for Robot Navigation in Unknown Terrain" | ||||||||||
| Eth_supermegabot | 70 | 4 years ago | 7 | Python | ||||||
| Instructions for ETH center for robotics summer school 2019. | ||||||||||
| Robotics D Star Lite | 46 | 13 years ago | 1 | C++ | ||||||
| D* Lite algorithm for partially known environments. | ||||||||||
| Offworld Gym | 45 | a year ago | 5 | gpl-3.0 | Python | |||||
| OffWorld Gym: Open-Access Physical Robotics Environment for Real-World Reinforcement Learning Benchmark and Research | ||||||||||
| Clf_reactive_planning_system | 23 | 2 years ago | agpl-3.0 | C++ | ||||||
| This package provides a CLF-based reactive planning system, described in paper: Efficient Anytime CLF Reactive Planning System for a Bipedal Robot on Undulating Terrain. The reactive planning system consists of a 5-Hz planning thread to guide a robot to a distant goal and a 300-Hz Control-Lyapunov-Function-based (CLF-based) reactive thread to cope with robot deviations. The planning system allowed Cassie Blue to autonomously traverse sinusoidally varying terrain. More experiments are still being conducted and this repo and the paper will be updated accordingly. | ||||||||||
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