zhm-real/MotionPlanning

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

2734 stars · 634 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python collection of motion planning and path tracking algorithms for autonomous vehicles, including Hybrid A*, Frenet Optimal Trajectory, State Lattice planners, and controllers like Pure Pursuit, Stanley, LQR, and MPC. It serves as an educational reference implementation with visual demos rather than production software.

Use cases

• implement hybrid A* path planning for autonomous vehicles
• learn path tracking controllers like pure pursuit and Stanley
• generate Frenet frame optimal trajectories
• simulate car and trailer vehicle models in Python
• study motion planning algorithms for self-driving cars
• compare LQR vs MPC steering controllers

When to choose

• learning or prototyping autonomous vehicle planning and control algorithms
• you want readable Python reference implementations with visualizations
• research or coursework on path planning and tracking

When to avoid

• production autonomous driving systems needing safety certification
• you need a maintained, licensed package (no license is provided)
• real-time embedded deployment

Facets

library · maturity maintenance

simulation machine-learning autonomous-vehicles robotics simulation python cross-platform motion-planning path-planning path-tracking hybrid-astar frenet-trajectory pure-pursuit stanley-controller lqr mpc autonomous-driving vehicle-models algorithm-visualization algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="zhm-real/MotionPlanning")