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Babysitter Motion Planning Skill

Sampling-based and optimization-based motion planning algorithms

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/robotics-simulation/skills/motion-planning" ~/.claude/skills/a5c-ai-babysitter-motion-planning-skill && rm -rf "$T"
manifest: library/specializations/robotics-simulation/skills/motion-planning/SKILL.md
tags
#motion-planning#trajectory-optimization#path-planning#robotics#planning-algorithms
source 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