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arXiv 2411.14701cs.RO
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用于行走仿真的具有软体足部的个性化3D人体数字孪生

Personalised 3D Human Digital Twin with Soft-Body Feet for Walking Simulation

School of Mechanical and Aerospace Engineering, Nanyang Technological University(南洋理工大学机械与航空航天工程学院);Rehabilitation Research Institute of Singapore (RRIS)(新加坡康复研究院)

Kum Yew Loke, Sherwin Stephen Chan, Mingyuan Lei, Henry Johan, Bingran Zuo, Wei Tech Ang

AI总结:

本文提出将基于真实运动捕捉数据生成的个性化软体足部集成到骨骼模型中,并用行走控制策略训练,实现了地面反作用力和关节角度均接近真实数据的动态精确人体数字孪生。

摘要:

随着辅助机器人在人类患者康复和辅助移动中的应用日益增多,人们需要更深入地理解人机交互,尤其是通过仿真在数字环境中理解这些交互。重点在于对这些仿真中的个性化3D人体数字孪生进行精确建模,以获取更多人机交互的见解。在本文中,我们提出将利用真实人体受试者运动捕捉数据生成的个性化软体足部集成到骨骼模型中,并用行走控制策略对其进行训练。通过使用地面反作用力和关节角度结果进行评估,软体足部能够生成与真实测量数据相当的地面反作用力结果,并紧密跟随裸骨骼模型和参考运动的关节角度结果。这为在仿真中生成由自身控制策略驱动的动态精确人体模型提供了一条有趣的途径,同时在训练过程中仅观察运动学信息。

英文摘要:

With the increasing use of assistive robots in rehabilitation and assisted mobility of human patients, there has been a need for a deeper understanding of human-robot interactions particularly through simulations, allowing an understanding of these interactions in a digital environment. There is an emphasis on accurately modelling personalised 3D human digital twins in these simulations, to glean more insights on human-robot interactions. In this paper, we propose to integrate personalised soft-body feet, generated using the motion capture data of real human subjects, into a skeletal model and train it with a walking control policy. Through evaluation using ground reaction force and joint angle results, the soft-body feet were able to generate ground reaction force results comparable to real measured data and closely follow joint angle results of the bare skeletal model and the reference motion. This presents an interesting avenue to produce a dynamically accurate human model in simulation driven by their own control policy while only seeing kinematic information during training.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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