Motion Planning Skill

SkillDev tools

Sampling-based and optimization-based motion planning algorithms

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

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