Converting Biomechanical Models from OpenSim to MuJoCo
Converting Biomechanical Models from OpenSim to MuJoCo
复制标题
将生物力学模型从 OpenSim 转换为 MuJoCo
DOI：
10.1007/978-3-030-70316-5_45
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Perttu Hämäläinen
中科院分区：
文献类型：
--
作者：
Aleksi Ikkala;Perttu Hämäläinen
OpenSim是一个广泛使用的生物力学模拟器，具有几个解剖学精确的人体肌肉骨骼模型。虽然OpenSim提供了有用的工具来分析人体运动，但它还不够快，无法常规用于新兴的研究方向，例如，通过深度神经网络和强化学习（RL）学习和模拟运动控制。我们提出了一个将OpenSim模型转换为MuJoCo的框架，MuJoCo是机器学习研究中事实上的模拟器，它本身缺乏准确的人体肌肉骨骼模型。我们表明，通过一些简单的解剖细节近似，OpenSim模型可以自动转换为运行速度快600倍的MuJoCo版本。我们还演示了一种计算优化MuJoCo模型参数的方法，以便两个模拟器的正演模拟产生相似的结果。
OpenSim is a widely used biomechanics simulator with several anatomically accurate human musculo-skeletal models. While OpenSim provides useful tools to analyse human movement, it is not fast enough to be routinely used for emerging research directions, e.g., learning and simulating motor control through deep neural networks and Reinforcement Learning (RL). We propose a framework for converting OpenSim models to MuJoCo, the de facto simulator in machine learning research, which itself lacks accurate musculo-skeletal human models. We show that with a few simple approximations of anatomical details, an OpenSim model can be automatically converted to a MuJoCo version that runs up to 600 times faster. We also demonstrate an approach to computationally optimize MuJoCo model parameters so that forward simulations of both simulators produce similar results.