Motion planning

Skill a5c-ai/babysitter/library/specializations/robotics-simulation/skills/motion-planning

Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration

Install

npx -y skills add a5c-ai/babysitter --skill motion-planning

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What its author says it does

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Sampling-based and optimization-based motion planning algorithms

SKILL.md

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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