SYS-zdk

SYS-zdk / robot_path_planner_public

Public
47
6
100% credibility
Found Mar 23, 2026 at 47 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
C++
AI Summary

A modular ROS1 workspace offering interchangeable global/local planners, controllers, trajectory optimizers, and costmap layers for reproducible mobile robot navigation research and development.

How It Works

1
🔍 Discover the robot navigation toolbox

You find this open toolbox that makes robots smartly avoid obstacles and follow paths in simulations.

2
💻 Set up on Ubuntu with ROS

Download and prepare it on your computer with simple setup steps—no coding needed.

3
🔨 Build everything

Run one easy command to compile all the pieces and get ready to go.

4
🚀 Launch the simulation

Start the demo and watch a robot move around maps with obstacles.

5
🤖 Swap planners and controllers

Pick different ways for the robot to plan paths and steer, seeing changes instantly.

6
⚙️ Tweak settings for your needs

Adjust speeds, safety margins, or behaviors to match your robot's world.

🎉 Robot navigates perfectly

Your robot smoothly avoids people, walls, and tight spaces every time.

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Star Growth

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AI-Generated Review

What is robot_path_planner_public?

robot_path_planner_public is a C++ library for ROS Noetic that delivers a modular toolbox for mobile robot path planning and navigation. It lets you snap together global and local planners, controllers, trajectory optimizers, and costmap layers like LEGO bricks, all in a single reproducible workspace with simulation maps and configs. Developers get plug-and-play stacks for everything from Voronoi-based global paths to MPC local control, slashing setup time for experiments.

Why is it gaining traction?

It stands out by bundling dozens of research-grade components—hybrid A*, MPPI controllers, reachability layers, social obstacle modeling—under one roof, with demo GIFs, param templates, and scripts to run benchmarks instantly. Unlike scattered single-planner repos, you swap modules via YAML IDs for apples-to-apples comparisons without rewiring ROS nav stacks. The public release of these battle-tested pipelines hooks robotics folks tired of forking upstream frameworks.

Who should use this?

ROS navigation engineers building autonomous mobile robots for warehouses or indoors, researchers reproducing motion planning papers (e.g., HPCC, Sunshine, ST-Planner), or teams evaluating custom path planners against baselines like HLP-MPC with corridors. Ideal if you're tuning Ackermann vehicles in Gazebo and need quick sim-to-real configs.

Verdict

Grab it if you're in ROS robot path planning—strong docs and modularity make it a solid starting point despite low 1.0% credibility from 47 stars. Still maturing (active dev, PRs welcome), but expect robust baselines over polished production code.

(198 words)

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