CARRT-运动捕捉数据用于机器人人体上部模型
Urvish Trivedi1, Redwan Alqasemi1, Rajiv Dubey1
1Department of Mechanical Engineering, University of South Florida, Tampa, FL 33620, USA.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
研究人员为机器人运动计划创建了一个详细的人类运动数据集. 这一公共数据集捕捉了日常生活活动,以在机器人系统中复制人类运动.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 生物力学 生物力学
- 人与计算机的交互
背景情况:
- 分析人类运动性能指标对于优化机器人系统至关重要.
- 在机器人中复制人类运动需要准确的人类运动数据和规划框架.
- 现有的方法往往缺乏用于全身人类运动捕捉的全面数据集.
研究的目的:
- 引入一套公开可用的数据集,介绍日常生活活动中人类全身运动的情况.
- 为开发和验证机器人运动规划框架提供数据.
- 为机器人应用程序创建特定主题的人类模型.
主要方法:
- 采集了详细的人体全身运动数据,使用Vicon运动捕捉系统.
- 记录了10名参与者的9项日常生活活动和8项运动范围活动.
- 处理的数据用于OpenSim (全身模型,关节角度) 和MATLAB (机器人模型).
主要成果:
- 产生了340个人类运动演示的综合数据集.
- 创建了特定的主体全身模型,并使用OpenSim计算了关节角度.
- 数据集包括原始 (.c3d),OpenSim (.trc) 和后处理的MATLAB兼容的运动数据.
结论:
- 发布的数据集使人类运动分析和机器人复制的先进研究成为可能.
- 该资源支持开发更复杂的辅助,康复和机器人技术.
- 公众对这些运动捕捉数据的访问加速了人机交互和运动规划方面的进展.
相关概念视频
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