Webots
Cyberbotics' Webots is an open source, multi-platform desktop application designed for modeling, programming, and simulating robots. It offers a comprehensive development environment that includes a vast asset library with robots, sensors, actuators, objects, and materials, facilitating rapid prototyping and efficient robotics project development. Users can import existing CAD models from tools like Blender or URDF and integrate OpenStreetMap data to create detailed simulations. Webots supports programming in multiple languages, including C, C++, Python, Java, MATLAB, and ROS, providing flexibility for diverse development needs. Its modern GUI, combined with a physics engine and OpenGL rendering, enables realistic simulation of various robotic systems, such as wheeled robots, industrial arms, legged robots, drones, and autonomous vehicles. The platform is widely utilized in industry, education, and research for tasks like robot prototyping, and AI algorithm development.
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Wayve
Wayve is an autonomous driving technology platform that develops AI foundation models to power next-generation self-driving vehicles through its Embodied AI approach. Wayve’s core innovation is a self-learning “AI driver” that enables vehicles to perceive, predict, and navigate complex real-world environments by learning from experience rather than relying on hand-coded rules or high-definition maps. Using primarily camera data and deep learning, the system builds a general-purpose driving intelligence that can adapt to new roads, cities, and vehicles with minimal retraining. Wayve’s mapless, hardware-agnostic architecture allows automakers to deploy advanced driver assistance and autonomous capabilities through software upgrades, supporting automation levels from L2+ to L4. It is designed to learn continuously from real-world and simulated data, enabling safe, natural driving behavior and improved handling of unexpected situations.
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Apollo Autonomous Vehicle Platform
Various sensors, such as LiDAR, cameras and radar collect environmental data surrounding the vehicle. Using sensor fusion technology perception algorithms can determine in real time the type, location, velocity and orientation of objects on the road. This autonomous perception system is backed by both Baidu’s big data and deep learning technologies, as well as a vast collection of real world labeled driving data. The large-scale deep-learning platform and GPU clusters. Simulation provides the ability to virtually drive millions of kilometers daily using an array of real world traffic and autonomous driving data. Through the simulation service, partners gain access to a large number of autonomous driving scenes to quickly test, validate, and optimize models with comprehensive coverage in a way that is safe and efficient.
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MORAI
MORAI offers a digital twin simulation platform that accelerates the development and testing of autonomous vehicles, urban air mobility, and maritime autonomous surface ships. Built with high-definition maps and a powerful physics engine, it bridges the gap between real-world and simulation test environments, providing all key elements for verifying autonomous systems, including autonomous driving, unmanned aerial vehicles, and unmanned ship systems. It provides a variety of sensor models, including cameras, LiDAR, GPS, radar, and Inertial Measurement Units (IMUs). Users can generate complex and diverse test scenarios from real-world data, including log-based scenarios and edge case scenarios. MORAI's cloud simulation allows for safe, cost-effective, and scalable testing, enabling multiple simulations to run concurrently and evaluate different scenarios in parallel.
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