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Back to atb033/multi_agent_path_planning

Open-source alternatives to Multi Agent Path Planning

30 open-source projects similar to atb033/multi_agent_path_planning, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Multi Agent Path Planning alternative.

  • ros-navigation/navigation2ros-navigation 的头像

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    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

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    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

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    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

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    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

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    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

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    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

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    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

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