Myoassist 0.1:用于仿生人的灵活性和敏捷性的Myosuite。

Chun Kwang Tan, Cheryl Wang, Shirui Lyu, Balint K Hodossy, Pierre Schumacher, Elizabeth B Wilson, Vittorio Caggiano, Vikash Kumar, Dario Farina, Letizia Gionfrida, Elliott J Rouse, Guillaume Durandau, Seungmoon Song
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引用次数: 0

摘要

准确可靠的数字孪生人类和可穿戴机器人可以彻底改变康复机器人。在这里,我们介绍MyoAssist 0.1,这是MyoSuite的一个子套件,专注于带有假肢和外骨骼等辅助设备的肌肉骨骼模拟环境。这个开源平台使研究和开发人机交互、控制策略和辅助机器人成为可能。我们提出了两个新的仿真环境:myoMPL具有带有机械义肢的截肢臂模型,myoOSL具有带有机械义肢的截肢腿模型。myoMPL环境为使用模块化假肢(MPL)的肩部截肢者提供了一个双手操作任务,其中任务是用生物手拿起物体,将其传递给假手,并将其放置在目标位置。myoOSL环境模拟了一个膝盖以上的截肢者使用开源腿部(OSL)来穿越具有挑战性的地形,如粗糙的表面、山丘和楼梯。尽管在模拟现实世界条件下人体和假肢系统的细微限制方面有一些简化,但这些环境提供了一个基础的仿真框架,支持肌肉骨骼动力学和辅助设备之间相互作用的跨学科研究。myoMPL和myoOSL都出现在NeurIPS会议的年度竞赛MyoChallenge中。所有代码都可以通过MyoSuite GitHub存储库访问。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Myoassist 0.1: Myosuite for Dexterity and Agility in Bionic Humans.

Accurate and reliable digital twins of humans and wearable robots can revolutionize rehabilitation robotics. Here, we introduce MyoAssist 0.1, a sub-suite of MyoSuite focused on musculoskeletal simulation environments with assistive devices such as prosthetics and exoskeletons. This open-source platform enables the study and development of human-device interactions, control strategies, and assistive robotics. We present two new simulation environments: myoMPL featuring an arm amputee model with a robotic prosthetic arm, and myoOSL featuring a leg amputee model with a robotic prosthetic leg. The myoMPL environment features a bimanual manipulation task for a shoulder disarticulation amputee using a Modular Prosthetic Limb (MPL), where the task is to pick up an object with the biological hand, pass it to the prosthetic hand, and place it at a target location. The myoOSL environment simulates an above-knee amputee using the Open-Source Leg (OSL) to traverse challenging terrains such as rough surfaces, hills, and stairs. Despite some simplifications in modeling the nuanced constraints of human and prosthetic systems under real-world conditions, these environments provide a foundational simulation framework that supports interdisciplinary research on the interplay between musculoskeletal dynamics and assistive devices. Both myoMPL and myoOSL are featured in MyoChallenge, an annual competition at the NeurIPS conference. All code is accessible through the MyoSuite GitHub repository.

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