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motion-planning

Generate browser-based Python code for robot motion planning algorithms.

Updated Dec 10, 2025
Search Tags:#PID#path planning#RRT#MPC#A*#trajectory optimization#motion planning
One-click install
npx skills add https://github.com/khanaleema/PhysicalAI-Book --skill motion-planning
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: motion-planning
Source: https://github.com/khanaleema/PhysicalAI-Book/tree/main/.gemini/skills/motion-planning
Command: npx skills add https://github.com/khanaleema/PhysicalAI-Book --skill motion-planning

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generates production-quality Python code for robot motion planning algorithms that run in Pyodide (browser). Provides educational, implementation-focused examples of path planning (A*, RRT), trajectory optimization, and control strategies (PID, MPC) with emphasis on visualization and teaching clarity.

Core Features & Use Cases

  • Path Planning Demos: Implement A*, RRT, and Dijkstra in browser-ready Python for interactive learning.
  • Trajectory Optimization: Demonstrate minimum-jerk and time-optimal trajectories.
  • Control Algorithms: Provide PID, MPC, and LQR examples for simulated robots.
  • Whole-Body Control Visualization: Explain task-space and null-space concepts with visualizations.
  • Educational Focus: Show-your-work style code with educational comments and plots.

Quick Start

Activate with prompts like:

  • "Create path planning code in the browser"
  • "Generate A* example for browser-based learning"
  • "Build PID controller for a simulated robot"

Frequently Asked Questions about motion-planning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement path planning algorithms like A* and RRT in a browser?▼

Path planning algorithms like A* and RRT can run directly in browsers using Pyodide, which executes Python code in WebAssembly. This Skill generates production-ready Python implementations with visualizations, letting you teach and test these algorithms interactively without server setup.

Can I generate trajectory optimization code that runs in the browser?▼

Yes. This Skill generates browser-compatible Python code for trajectory optimization, including minimum-jerk and time-optimal trajectories. The code includes comprehensive type hints, docstrings, and ready-to-run templates with built-in visualizations for educational clarity.

What control algorithms can I implement for robot motion planning?▼

You can implement PID controllers, model predictive control (MPC), and LQR for simulated robots, along with whole-body control demonstrations showing task-space and null-space concepts. All code is generated in Pyodide-compatible Python with educational comments and plots.

Is Pyodide required to run motion planning code, or can it work elsewhere?▼

This Skill generates code specifically for Pyodide environments, which run Python in browsers via WebAssembly. The code is production-quality Python and includes comprehensive error handling, making it portable, but Pyodide enables the browser-based interactive learning experience this Skill targets.

How detailed are the generated implementations of Dijkstra and RRT algorithms?▼

Implementations are advanced in depth—they include full algorithm reasoning, production-quality error handling, comprehensive type hints, and detailed docstrings. Code is designed for teaching and demonstration, with emphasis on clarity and ready-to-run templates rather than minimal examples.

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