smac-planner-hybrid-a-star

Configure Nav2 SMAC Hybrid-A* planner parameters for kinematically feasible paths.

18|2|Updated Apr 20, 2026
One-click install
npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill smac-planner-hybrid-a-star
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: smac-planner-hybrid-a-star
Source: https://github.com/wimblerobotics/ros2-copilot-skills/tree/main/smac-planner-hybrid-a-star
Command: npx skills add https://github.com/wimblerobotics/ros2-copilot-skills --skill smac-planner-hybrid-a-star

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SMAC Hybrid-A* planner provides non-holonomic, kinematically feasible path planning for ROS 2 Nav2 by extending A* into SE(2) with motion primitives and a closed-form analytic expansion when possible.

Core Features & Use Cases

  • Supports planning in SE(2) using discretized headings and motion primitives (DUBIN/REEDS_SHEPP) to produce executable paths for differential drive and Ackermann robots.
  • Exposes tunable parameters such as minimum_turning_radius, motion_model_for_search, angle_quantization_bins, analytic_expansion_ratio, and lookup_table_size to balance speed and path quality.
  • Useful for docking, parking, and navigating tight corridors where non-holonomic constraints are critical for safe, feasible trajectories.

Quick Start

Configure the planner in Nav2 with your robot's parameters and run a planning request on a sample map.

Frequently Asked Questions about smac-planner-hybrid-a-star

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

FAQPage Schema
How do I plan kinematically feasible Nav2 paths for Ackermann robots?

To plan kinematically feasible Nav2 paths for Ackermann robots, configure a SMAC Hybrid-A* planner using SE(2) motion primitives like REEDS_SHEPP to generate executable trajectories.

What is Hybrid-A* path planning in ROS 2 used for?

Hybrid-A* path planning in ROS 2 extends A* into SE(2) with motion primitives to generate non-holonomic, kinematically feasible paths for navigating tight corridors, docking, and parking maneuvers.

How do I configure minimum turning radius constraints in Nav2 motion planning?

Configure minimum turning radius constraints in Nav2 motion planning by tuning YAML parameters like minimum_turning_radius and motion_model_for_search within the SMAC Hybrid-A* planner to balance speed and trajectory quality.

Can SMAC Hybrid-A* handle differential drive robots in cluttered maps?

SMAC Hybrid-A* handles differential drive robots in cluttered maps by using discretized headings and analytic expansion to satisfy non-holonomic constraints for safe, feasible trajectories.

What is the best way to balance speed and path quality in non-holonomic motion planning?

Balance speed and path quality in non-holonomic motion planning by adjusting YAML-driven parameters such as angle_quantization_bins, analytic_expansion_ratio, and lookup_table_size within the SMAC Hybrid-A* planner.

Why does my Nav2 path planner ignore minimum turning radius constraints?

Nav2 path planners ignore minimum turning radius constraints when not configured for non-holonomic planning; setting SMAC Hybrid-A* with proper motion_model_for_search and minimum_turning_radius parameters enforces feasible trajectories.