For path planning algorithms, the strongest matches are zhm-real/pathplanning (PathPlanning provides implementations of graph-based search and sampling-based planning), atb033/multi_agent_path_planning (This repository provides a comprehensive Python toolkit for multi-agent) and ai-winter/ros_motion_planning (This project is a comprehensive library and framework for). zhm-real/motionplanning and ros-planning/navigation2 round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
Hand-picked open-source path planning algorithms for robotics and AI, ranked by GitHub stars and activity. Compare and pick the right one.
PathPlanning is a library of animated path planning algorithms that includes implementations of A-star, Dijkstra, RRT, and spline-based trajectory generation for both 2D and 3D environments. The project provides a collection of motion planning algorithms that demonstrate how robots can find collision-free paths through continuous spaces, with each algorithm rendered as a step-by-step visual animation to show how the search or tree grows over time. The library covers three main categories of path planning: sampling-based methods like RRT, RRT-star, and BIT-star that grow trees by randomly samp
PathPlanning provides implementations of graph-based search and sampling-based planning algorithms with step-by-step visualizations, making it a useful library for robotics and navigation even though it omits some advanced features like multi-agent path finding.
This library is a comprehensive toolkit for autonomous robot navigation and multi-agent motion coordination. It provides a framework for calculating collision-free movement trajectories, enabling multiple robots to operate within shared environments while maintaining efficient and safe paths. The project distinguishes itself by supporting both global and decentralized control strategies. It offers global coordination techniques that resolve path conflicts across entire workspaces to ensure unified group movement, alongside decentralized methods that allow individual agents to react dynamicall
This repository provides a comprehensive Python toolkit for multi-agent path planning, motion coordination, and collision avoidance in robotics and autonomous navigation.
This project is a comprehensive library and framework for autonomous mobile robot navigation, providing a suite of geometric, heuristic, and optimization-based algorithms. It enables robots to calculate collision-free global paths and generate smooth, kinematically feasible local trajectories within complex environments. The system is built on a modular plugin architecture that allows developers to integrate and configure custom motion planning algorithms directly into the Robot Operating System. By utilizing a layered spatial representation, the framework aggregates heterogeneous sensor data
This project is a comprehensive library and framework for autonomous robot navigation featuring graph-based search, sampling-based planners, collision checking, and local trajectory generation, which directly matches the motion planning requirements.
MotionPlanning is a software library designed for autonomous navigation, providing a comprehensive suite of tools for path planning, trajectory generation, and vehicle control. It enables the calculation of collision-free routes and dynamic movement paths for autonomous vehicles operating in complex, changing environments. The project distinguishes itself by integrating hierarchical motion decomposition, which separates high-level route planning from low-level trajectory generation to manage computational complexity. It employs kinematic bicycle modeling and trailer dynamics simulation to ens
This Python library provides a comprehensive suite of path planning, trajectory generation, and motion planning algorithms tailored for autonomous vehicles and robotics navigation.
Navigation2 is a navigation stack for ROS 2 designed for autonomous robot navigation. It provides a framework for computing optimal paths from a starting position to a goal while avoiding static and dynamic obstacles. The system utilizes a behavior tree orchestrator to coordinate complex navigation tasks and trigger recovery actions. Its architecture is plugin-based, allowing planners, controllers, and costmap layers to be swapped at runtime without recompiling the core system. The project covers path planning, motion control, and environmental mapping. It generates occupancy grids and costm
Navigation2 is a comprehensive autonomous robot navigation framework that provides global path planning, local motion control, collision checking, and costmap-based obstacle avoidance.
Teblocalplanner is a robot navigation package and local planner that computes collision-free trajectories for mobile robots in dynamic environments. The software operates as a navigation algorithm designed to calculate optimal paths by continuously balancing execution time, kinematic limits, obstacle clearance, and trajectory smoothness within a moving time window. The system utilizes timed-elastic-band optimization to treat trajectories as elastic bands that deform based on environmental constraints and obstacles. It incorporates graph-based topology generation to explore distinct homotopy
This repository provides a specialized local path planner for mobile robots using timed-elastic-band optimization, fitting the navigation and obstacle avoidance aspects of the search while focusing on local trajectory generation rather than a full multi-algorithm library.
PythonRobotics is a comprehensive collection of modular robotics algorithms and educational simulations designed for autonomous navigation, state estimation, and motion control. The project provides a library of standalone implementations for path planning, localization, mapping, and kinematics, serving as a resource for researchers and students to experiment with foundational and advanced robotic theories. The project distinguishes itself through an algorithm-centric design where each module functions as an isolated script, allowing for independent testing and clear pedagogical demonstration
PythonRobotics is a comprehensive collection of modular algorithms for autonomous navigation and path planning, providing educational implementations of graph-based search, sampling-based planners, and collision checking suited for robotics experimentation.
This project is a framework for autonomous mobile robot navigation within the Robot Operating System ecosystem. It provides a suite of tools for calculating safe trajectories and movement commands, enabling mobile bases to reach specific destinations while avoiding obstacles in dynamic environments. The system utilizes a hierarchical planning approach that separates long-range path generation from short-range reactive obstacle avoidance. It maintains spatial awareness through a centralized coordinate tracking system and a grid-based representation that stores obstacle information and proximit
This repository is a comprehensive autonomous mobile robot navigation framework that provides hierarchical path planning and reactive obstacle avoidance suited for robotics development.
PathFinding.js is a grid-based pathfinding library that implements multiple search algorithms for computing optimal routes on 2D maps. It provides implementations of A*, Dijkstra, Breadth-First Search, and Jump Point Search, each designed to find the shortest path between two points on a grid while avoiding obstacles. The library is built around a pluggable architecture where each pathfinding strategy shares a common interface, allowing algorithms to be selected at runtime without modifying core logic. It includes a configurable diagonal movement rule engine that controls diagonal traversal b
PathFinding.js provides graph-based search algorithms like A* and Dijkstra on a grid for pathfinding, though it lacks the sampling-based planners and advanced motion planning features required for full autonomous navigation.
This project is a comprehensive software framework for autonomous robot navigation, providing a collection of algorithms for path planning, motion control, and trajectory generation. It serves as a toolkit for implementing and researching navigation logic, enabling the calculation of collision-free routes and the execution of precise movement commands for autonomous mobile agents. The library distinguishes itself by integrating both global pathfinding and real-time reactive control strategies. It supports diverse planning methodologies, including graph-based heuristic searches and sampling-ba
This project provides a Python implementation of path planning and motion planning algorithms with graph-based searches and sampling-based planners, though it lacks multi-agent path finding and some advanced kinodynamic features.
Ego-planner-swarm is an autonomous drone swarm trajectory planner and decentralized multi-agent navigation system. It provides algorithmic software tools for calculating collision-free movement paths for single or multiple multicopters using decentralized onboard computing and local peer communication without relying on central ground stations or servers. The software encompasses algorithmic components for drone motion planning, including asynchronous background replanning loops that adapt flight paths immediately to newly perceived obstacles or moving agents. Movement paths are represented
Ego-planner-swarm is a decentralized multi-agent trajectory planning system that provides gradient-based optimization and collision avoidance for autonomous drones, fitting the category well despite being tailored specifically to aerial swarm navigation rather than a general-purpose library.
Navigation2 is a ROS 2 navigation framework for autonomous mobile robots. It provides the core identity of a path planner, costmap management system, kinematic motion controller, and behavior tree orchestrator to compute collision-free routes and execute movement commands. The framework is distinguished by its use of behavior trees to coordinate modular task servers, enabling complex navigation routines and autonomous recovery actions. It supports a plugin-based architecture that allows planners and controllers to be swapped at runtime to adapt to different environments. The system covers a
This repository provides a complete ROS 2 autonomous navigation framework that implements path planning, collision-avoidance costmaps, and motion control, though it serves as a full framework rather than a standalone algorithmic library.
RecastNavigation is a navigation mesh toolset and game AI pathfinding library used to generate and query walkable surfaces in 3D environments. It functions as a runtime navigation mesh generator and spatial query library, transforming raw 3D geometry into simplified surfaces to enable AI movement. The project includes a crowd simulation engine that manages steering and collision avoidance for large numbers of agents. It provides capabilities for group movement coordination and the simulation of many agents simultaneously using scalable navigation techniques. The system covers mesh generation
RecastNavigation is a navigation mesh toolset and pathfinding library that handles spatial queries and crowd collision avoidance, though it focuses primarily on navmesh generation rather than covering the full breadth of sampling-based planners and multi-agent path finding.
| 仓库 | Star 数 | 语言 | 许可证 | 最后推送 |
|---|---|---|---|---|
| zhm-real/pathplanning | 9.3K | Python | MIT | |
| atb033/multi_agent_path_planning | 1.5K | Python | MIT | |
| ai-winter/ros_motion_planning | 3.5K | C++ | GPL-3.0 | |
| zhm-real/motionplanning | 2.7K | Python | — | |
| ros-planning/navigation2 | 4.4K | C++ | NOASSERTION | |
| rst-tu-dortmund/teb_local_planner | 1.3K | C++ | BSD-3-Clause | |
| atsushisakai/pythonrobotics | 29.8K | Python | NOASSERTION | |
| ros-planning/navigation | 2.6K | C++ | — | |
| qiao/pathfinding.js | 8.7K | JavaScript | — | |
| ai-winter/python_motion_planning | 1K | Python | GPL-3.0 |