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走向多忠实数字人体模型,用于用于触觉人机交互的模拟环境

Rajarshi Roy¹, Qianwen Zhao², Aldrin Padua²

¹Corvid Technologies, Mooresville, NC 28117, United States.

Military medicine

|September 23, 2025

概括

一个新的多效率数字人体模型 (M-DHM) 集成了低效率和高效率模型,以实现更安全的机器人伤亡提取. 这种先进的模拟工具增强了用于救援任务的人机交互规划.

科学领域:

机器人和自主系统 (RAS)
人与机器人的交互 (HRI)
计算生物力学计算生物力学

背景情况:

越来越多的人对RAS感兴趣,用于战场伤亡人员的提取和医疗干预.
目前的数字人体模型 (DHM) 缺乏生物真实性和可扩展性的机器人模拟.
在机器人操纵中需要精确的人类建模,以防止在人机交互 (HRI) 期间进一步受伤.

研究的目的:

开发一个适合机器人模拟环境的多忠实数字人体模型 (M-DHM).
将低保真多体动态 (MD) DHM与高保真有限元 (FE) DHM集成.
在HRI事件期间为路径规划人员提供点和分布式加载数据.

主要方法:

开发了一个软件架构,集成两个低保真MD-DHM和一个高保真FE-DHM.
实现了MD-DHM和FE-DHM之间的人体关节动力学和应用力的交换.
开发了检索多忠度解剖负载 (M-AL) 的方法,并使用减少顺序模型进行估计.

主要成果:

成功演示了M-DHM用于下臂的抓取和触摸.
在模拟中验证了重新定位和拖动腿部的模型.
展示了该模型能够为HRI规划提供全面的负载数据的能力.

结论:

M-DHM为机器人应用程序推进了下一代规划算法.
潜在的军事应用,如搜救任务.
未来的民用应用包括用于病人操纵和医疗保健的RAS.

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