Motion Planning Skill
SkillDev toolsSampling-based and optimization-based motion planning algorithms
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Motion Planning Skill skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/robotics-simulation/skills/motion-planning/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
motion-planning-skill- Source
- github.com/a5c-ai/babysitter