Robot navigation simulator

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

Habitat-Lab is an open-source platform for training and evaluating embodied AI agents in photorealistic 3D indoor environments. It functions as a high-performance 3D indoor environment simulator that supports physics-based interaction, enabling research into navigation and manipulation tasks. The platform provides a modular task-environment abstraction that separates task logic from environment simulation, using configuration-driven pipeline assembly to compose simulation and training pipelines. It includes a hierarchical sensor-actuator architecture for mixing and matching perception and act

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

AirSim is a high-fidelity simulation platform designed for the development and testing of autonomous vehicles. Built as a plugin for game engines, it provides a physics-based environment that models vehicle dynamics and sensor data, serving as a foundation for robotics research, computer vision training, and reinforcement learning. The platform distinguishes itself through its support for hardware-in-the-loop and software-in-the-loop testing, allowing developers to validate control logic and firmware against real-world signals or concurrent processes. It offers extensive programmatic control

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

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

CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving software. It functions as an urban traffic simulator that generates realistic vehicle and pedestrian behavior and as a synthetic sensor data generator producing LiDAR, Radar, and camera data. The platform distinguishes itself through its deep integration with robotics frameworks, specifically providing native connectivity to ROS2 nodes for robotic control and data processing. It supports the training of driving models via imitation and reinforcement learning within a controlle

Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents within photorealistic indoor and outdoor environments. It serves as a simulator for AI and robotics, providing a system for generating synthetic data and simulating physical interactions. The project is distinguished by a native C++ core that enables high-throughput simulation and a rendering pipeline using physically based rendering and baked global illumination. It features a navigation system based on pre-computed navigation meshes to ensure collision-free traversal and a rigi

Gazebo - A dynamic multi-robot simulator

A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles

The Modular OpenRobots Simulation Engine

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

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

Prometheus is an autonomous drone flight stack providing a software suite for navigation, target recognition, and flight control. It functions as a computer vision navigation engine and a precision autonomous landing controller, enabling unmanned aerial vehicles to operate without manual pilot input. The system distinguishes itself through multi-vehicle coordination and swarm synchronization, allowing aerial and ground vehicles to maintain formations and execute joint maneuvers via a shared communication framework. It further integrates a simulation environment for software-in-the-loop testin

The project provides a software simulation framework and physics engine for modeling underwater vehicles, subsea sensors, and ocean environments. It runs within robotics middleware to test autonomous and remotely operated underwater vehicles by combining hydrodynamic physics, ocean currents, and sensor modeling. The platform computes hydrodynamic forces, buoyancy, equations of motion, and thruster dynamics to accurately replicate underwater physics. It loads pre-configured mechanical assemblies, manipulator panels, and environmental sensors, while generating three-dimensional water movement f

IsaacGymEnvs is a GPU-accelerated physics sandbox and robotics policy training suite designed for reinforcement learning. It serves as a vectorized robotic simulator that runs thousands of parallel environments on GPUs to accelerate the training of neural networks. The project provides a sim-to-real transfer framework that utilizes domain randomization and physics variations to ensure policies trained in simulation are robust enough for deployment on real hardware. It distinguishes itself through a high-performance architecture that uses tensor-based state management to handle observations an

Lab is a customizable 3D platform and research testbed designed for training and testing autonomous agents using reinforcement learning. It serves as a spatial AI training simulator where agents can be evaluated through navigation and puzzle-solving tasks. The environment allows for the definition of complex layouts and task behaviors through external scripting, enabling the generation of specific challenges for AI research. It supports both automated training via standard API bindings and manual agent control to validate simulation dynamics. The system utilizes a grid-based spatial represen

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

Central repository for tools, tutorials, resources, and documentation for robotics simulation in Unity.

Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version

DRL-robot-navigation is a deep reinforcement learning platform and robotic simulation framework designed to train autonomous mobile robots for collision-free path planning. It uses neural network policies and physics-engine simulation environments to teach robots how to navigate toward target coordinates while avoiding obstacles. The software trains continuous control policies using twin delayed deep deterministic policy gradients over continuous state and action spaces. Training is guided by scalar reward signals derived from target proximity and obstacle avoidance distances. System compone

Rotors Simulator is a physics-based simulation framework designed for testing multirotor unmanned aerial vehicles and their control algorithms within a virtual environment. It models aerial vehicle movement, rotor thrust, and aerodynamic interactions by computing individual motor speeds directly to apply thrust and torque forces to rigid body dynamics. Aircraft kinematics, visual meshes, and sensor attachment points are described declaratively using unified robot description format files. The environment integrates dynamic models and aerodynamic forces through native runtime plugins while coo