motion-planning-skill

Solid

Sampling-based and optimization-based motion planning algorithms

AI & Automation 814 stars 53 forks Updated today MIT

Install

View on GitHub

Quality Score: 96/100

Stars 20%
97
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
64
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Motion Planning Skill ## Overview Expert skill for implementing and configuring motion planning algorithms, including sampling-based planners (OMPL) and optimization-based trajectory planners. ## Capabilities - Configure OMPL planners (RRT, RRT*, RRT-Connect, PRM, FMT*) - Implement hybrid A* for car-like robots - Set up lattice-based planners - Configure trajectory optimization (TrajOpt, CHOMP, STOMP) - Implement time-optimal trajectory planning - Set up path smoothing algorithms - Configure state space and validity checking - Implement kinodynamic planning - Set up multi-query planning with roadmaps - Configure asymptotically optimal planners ## Target Processes - path-planning-algorithm.js - trajectory-optimization.js - moveit-manipulation-planning.js - nav2-navigation-setup.js ## Dependencies - OMPL (Open Motion Planning Library) - MoveIt - TrajOpt - FCL (Flexible Collision Library) ## Usage Context This skill is invoked when processes require path planning algorithm selection, trajectory optimization, or custom motion planning solutions. ## Output Artifacts - OMPL planner configurations - State space definitions - Validity checker implementations - Trajectory optimization setups - Path smoothing configurations - Planning benchmark results

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

Related Skills