Projects sharing features with Webots

dm_control is a physics-based simulation framework and robot control simulation toolkit designed for creating and interacting with continuous control tasks. It serves as a suite of reinforcement learning environments and a benchmarking tool for evaluating autonomous agents within virtual physics spaces. The framework provides a collection of environments based on MuJoCo physics bindings to simulate rigid body dynamics and contact forces. It features hardware-accelerated rendering and interactive viewers for the visualization of physics environments and agent behavior. The system supports the

Isaac Lab is an open-source framework for training robot policies in physically simulated environments, supporting both single-agent and multi-agent reinforcement learning. It is built on an Omniverse-PhysX simulation backend that models rigid bodies, articulated systems, deformable objects, and sensors, and provides a task-based environment configuration system where each training environment is defined as a modular class specifying observation spaces, action spaces, reward functions, and termination conditions. The framework distinguishes itself through an RL-library abstraction layer that

OM1 is a multimodal AI agent runtime and orchestration framework designed to connect large language models to physical robot hardware and sensors. It provides an execution environment that processes audio, video, and sensor data to drive autonomous decisions and actions in real-world settings. The system integrates a robotics SLAM and navigation stack with a hardware abstraction layer, allowing high-level AI commands to be translated into low-level motor and actuator instructions. It distinguishes itself by incorporating blockchain-based governance to enforce immutable operational rules and p

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

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

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

Rapier is a cross-platform physics engine and rigid body dynamics solver designed for 2D and 3D simulations. It functions as a collision detection system and a robotics simulation framework, providing a consistent API for calculating physical interactions across different environments. The engine distinguishes itself with specialized robotics capabilities, including a toolkit for importing URDF and STL models to control multibody chains. It supports precise mechanical movement through inverse kinematics calculations and the application of PID controllers for dynamic body control. The simulat

Genesis is an embodied AI simulation platform and parallelized robotics simulator designed for training general-purpose robotic agents. It integrates a physics engine for robotics that calculates collisions and movements for rigid bodies, soft tissues, and fluids, alongside a photorealistic 3D rendering engine. The platform features a domain randomization framework to vary environment parameters across parallel simulations, aiding in sim-to-real transfer. It supports the integration of real-world captured light fields and Gaussian splatting to provide photorealistic backgrounds within simulat

Oasis is an LLM-powered multi-agent social simulator and research tool designed to study synthetic social phenomena. It functions as a synthetic social network platform, replicating the infrastructure of social sites including user profiles, follow relationships, and content discovery mechanisms to model human-like social behaviors at scale. The framework orchestrates large-scale agent populations, supporting up to one million autonomous agents. It distinguishes itself by translating language model outputs into concrete social actions and external tool executions through a tool-calling orches

The Open-Source Rover Platform is a hardware and software framework for building and controlling six-wheel planetary exploration rovers. It provides a six-wheel robot chassis and a modular robotics framework designed for integrating various motors, wheel sizes, and chassis materials. The platform features a six-wheel chassis equipped with a differential pivot suspension and an Ackerman steering mechanism to enable navigation across rugged outdoor terrain. Control is managed through a communication system that connects central processors to hardware via Bluetooth, WiFi, or USB for remote opera

This project provides a complete set of design files and hardware specifications for a 3D-printable industrial-style robot arm. The system includes a CAN bus robot controller for managing stepper motors and sensors, a kinematics engine for calculating joint angles and poses, and a UDP-based Python API for sending motion commands and monitoring telemetry. The system features a force-controlled robotic gripper that utilizes field-oriented control on stepper motors to enable compliant grasping and precise force sensing. It also includes a 3D position visualization tool for real-time telemetry tr

OpenCat-Quadruped-Robot is a development framework and motion control API for building four-legged robots. It provides a comprehensive environment for quadruped robot development, featuring tools for locomotion gait design, inverse kinematics, and a layered control architecture that separates high-level intelligence from low-level motion. The project distinguishes itself as an embedded AI deployment tool, allowing users to train, quantize, and deploy machine learning models to vision modules for tasks such as object detection and visual target tracking. It further supports complex human-robot

Unitree RL Gym is an integrated software framework designed for the simulation, training, and deployment of motion control policies for legged robotic platforms. It provides a comprehensive environment for developing locomotion strategies for quadruped and humanoid robots by leveraging reinforcement learning algorithms within high-fidelity physics-based simulations. The platform distinguishes itself by offering an end-to-end workflow that bridges the gap between virtual training and physical execution. It includes specialized tools for mapping raw sensor data into normalized state-space obser

Legged Gym is a high-performance simulation platform and toolkit engineered for training autonomous robotic agents in complex, physics-based environments. It provides a comprehensive framework for developing legged locomotion control policies, enabling robots to learn movement strategies for navigating uneven terrain and managing physical disturbances through reinforcement learning. The platform distinguishes itself by utilizing hardware-accelerated physics and headless execution to maximize computational throughput during training. It incorporates a domain randomization pipeline that injects

pysc2 is a Python interface and simulation framework that connects the StarCraft II game engine to machine learning agents. It acts as an API wrapper that exposes game internals as a set of observations and actions, providing a reinforcement learning environment for research and training. The framework includes tools for game replay analysis to extract data and sequences of actions from recorded matches for predictive modeling. It also provides an agent simulation environment to run and evaluate the performance of single or competing artificial intelligence agents. The system handles game ma

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 is an AI research implementation library and machine learning research repository. It provides a collection of reference code, illustrative implementations, and open-source research datasets used to verify hypotheses and build upon existing models in artificial intelligence. The repository focuses on scientific research reproduction by translating theoretical findings from published papers into executable code. It includes specialized scientific simulation environments designed to test the behavior of autonomous agents and models within controlled settings. The project covers AI

MuJoCo is a physics simulation engine designed for the dynamics of multi-joint articulated structures. It provides a computational framework for calculating the forces, velocities, and physical interactions of complex models within a virtual environment, supporting research in robotics, biomechanics, and machine learning. The engine utilizes a constraint-based dynamics solver and recursive algorithms to manage the motion of articulated systems. It includes a native graphical interface for real-time visualization, allowing users to inspect physical behaviors and contact dynamics as they occur.

ICCV 2025 Highlights Large-scale photo-realistic virtual worlds for embodied AI

SUMO is a microscopic traffic simulation suite designed to model the movement of individual vehicles and pedestrians across large-scale urban road networks. It functions as a multimodal transport simulator that integrates cars, pedestrians, bicycles, railways, and waterways within a single environment, supported by tools for road network generation and traffic demand modeling. The project distinguishes itself through specialized toolsets for environmental impact analysis, which calculate vehicle emissions and energy consumption for electric and hybrid fleets. It provides comprehensive capabil

Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving

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

Computational framework for reinforcement learning in traffic control

ROS bridge for CARLA Simulator

MIT Cheetah I Implementation

Generate random crop fields for Ignition Gazebo