Showing 4 open source projects for "control simulator"

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  • 1
    CARLA Simulator

    CARLA Simulator

    Open-source simulator for autonomous driving research.

    CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites, environmental conditions, full control of all static and dynamic actors, maps generation and much more. Multiple clients...
    Downloads: 43 This Week
    Last Update:
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  • 2
    Bullet Physics SDK

    Bullet Physics SDK

    Real-time collision detection and multi-physics simulation for VR

    This is the official C++ source code repository of the Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. We are developing a new differentiable simulator for robotics learning, called Tiny Differentiable Simulator, or TDS. The simulator allows for hybrid simulation with neural networks. It allows different automatic differentiation backends, for forward and reverse mode gradients. TDS can be trained...
    Downloads: 4 This Week
    Last Update:
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  • 3
    AirSim

    AirSim

    A simulator for drones, cars and more, built on Unreal Engine

    ...AirSim's development is oriented towards the goal of creating a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles. For this purpose, AirSim also exposes APIs to retrieve data and control vehicles in a platform independent way. AirSim is fully enabled for multiple vehicles. This capability allows you to create multiple vehicles easily and use APIs to control them.
    Downloads: 40 This Week
    Last Update:
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  • 4
    This project intends to create a bacteria simulator framework, with some realistic bacteria control methods based on chemical signaling, simple sensors, motors and neural networks. The bacteria will evolve in a genetic algorithm environment.
    Downloads: 0 This Week
    Last Update:
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