5 projects for "physics simulations" with 2 filters applied:

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  • 1
    Brax

    Brax

    Massively parallel rigidbody physics simulation

    Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization.
    Downloads: 1 This Week
    Last Update:
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  • 2
    ManiSkill

    ManiSkill

    SAPIEN Manipulation Skill Framework

    ManiSkill is a benchmark platform for training and evaluating reinforcement learning agents on dexterous manipulation tasks using physics-based simulations. Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios.
    Downloads: 1 This Week
    Last Update:
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  • 3
    RL Games

    RL Games

    RL implementations

    rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch.
    Downloads: 0 This Week
    Last Update:
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  • 4
    robosuite

    robosuite

    A Modular Simulation Framework and Benchmark for Robot Learning

    Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning.
    Downloads: 0 This Week
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  • 5
    CORL

    CORL

    High-quality single-file implementations of SOTA Offline

    CORL (Collection of Reinforcement Learning Environments for Control Tasks) is a modular and extensible set of high-quality reinforcement learning environments focused on continuous control and robotics. It aims to offer standardized environments suitable for benchmarking state-of-the-art RL algorithms in control tasks, including physics-based simulations and custom-designed scenarios.
    Downloads: 0 This Week
    Last Update:
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