Webots is a free and open-source 3D robot simulator developed by Cyberbotics. It is designed to model, simulate, and control mobile robots, manipulators, and drones in complex physical environments. Widely used in education, academic research, and industry, Webots supports realistic physics, customizable robots, and integration with AI frameworks.

The simulator allows users to prototype and test algorithms for control, perception, and reinforcement learning before deploying to physical robots. It includes a library of prebuilt robot models, supports multiple programming languages, and provides seamless integration with real-world robot platforms.

Key benefits:

• Realistic physics and environment modeling

• Extensive support for robot hardware and sensors

• Cross-platform, open source, and continuously maintained

What are the main features of Webots?

Comprehensive robot simulation engine

Webots enables high-fidelity simulation of robots in 3D environments using the Open Dynamics Engine (ODE) for physics.

• Supports wheeled robots, quadrupeds, humanoids, manipulators, and drones

• Simulates collisions, contacts, and realistic dynamics

• Includes a wide variety of 3D objects and terrain elements

Rich sensor and actuator support

The platform provides virtual equivalents for most robotic components, allowing testing of perception and control systems.

• Simulated sensors: cameras (RGB, depth), LiDAR, IMU, GPS, microphones

• Actuators: motors, servos, LEDs, grippers, propellers

• Sensor noise modeling for realistic performance testing

Multi-language programming and API support

Users can control robots using C, C++, Python, Java, MATLAB, and ROS, making it versatile for different workflows.

• Built-in development environment with real-time simulation

• ROS 2 integration for bridging with real-world robotics ecosystems

• Web interface support for remote access and control

AI and reinforcement learning integration

Webots can be used in machine learning workflows for training agents in robotics-related tasks.

• Compatible with Python ML libraries (e.g., TensorFlow, PyTorch)

• Used in deep reinforcement learning for locomotion, vision, and manipulation

• Supports curriculum learning and multi-agent scenarios

Real-to-sim and sim-to-real capabilities

The simulator is designed to mirror real-world hardware, enabling better transferability of models between simulation and physical deployment.

• Supports exporting controllers to real robots (e.g., Raspberry Pi, NVIDIA Jetson)

• Realistic sensor data for perception model training

• Scalable experiments with parallel simulation runs

Why choose Webots?

• Comprehensive and realistic simulation for a wide range of robotic systems

• Open-source and actively developed, with community and commercial backing

• Flexible programming and integration options, supporting major languages and tools

• Ideal for research, teaching, and prototyping, from basic robotics to advanced AI

• Strong support for transfer to real hardware, including ROS-compatible devices