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CARRT 运动捕捉数据用于机器人人体上身模型。

CARRT-Motion Capture Data for Robotic Human Upper Body Model.

机构信息

Department of Mechanical Engineering, University of South Florida, Tampa, FL 33620, USA.

出版信息

Sensors (Basel). 2023 Oct 10;23(20):8354. doi: 10.3390/s23208354.

Abstract

In recent years, researchers have focused on analyzing humans' daily living activities to study various performance metrics that humans subconsciously optimize while performing a particular task. In order to recreate these motions in robotic structures based on the human model, researchers developed a framework for robot motion planning which is able to use various optimization methods to replicate similar motions demonstrated by humans. As part of this process, it will be necessary to record the motions data of the human body and the objects involved in order to provide all the essential information for motion planning. This paper aims to provide a dataset of human motion performing activities of daily living that consists of detailed and accurate human whole-body motion data collected using a Vicon motion capture system. The data have been utilized to generate a subject-specific full-body model within OpenSim. Additionally, it facilitated the computation of joint angles within the OpenSim framework, which can subsequently be applied to the subject-specific robotic model developed MATLAB framework. The dataset comprises nine daily living activities and eight Range of Motion activities performed by ten healthy participants and with two repetitions of each variation of one action, resulting in 340 demonstrations of all the actions. A whole-body human motion database is made available to the public at the Center for Assistive, Rehabilitation, and Robotics Technologies (CARRT)-Motion Capture Data for Robotic Human Upper Body Model, which consists of raw motion data in .c3d format, motion data in .trc format for the OpenSim model, as well as post-processed motion data for the MATLAB-based model.

摘要

近年来,研究人员专注于分析人类的日常活动,以研究人类在执行特定任务时潜意识优化的各种性能指标。为了在基于人体模型的机器人结构中重现这些动作,研究人员开发了一种机器人运动规划框架,该框架能够使用各种优化方法复制人类演示的类似动作。在这个过程中,有必要记录人体和涉及的物体的运动数据,以便为运动规划提供所有必要的信息。本文旨在提供一个人类日常活动运动的数据集,其中包含使用 Vicon 运动捕捉系统收集的详细准确的人体全身运动数据。这些数据已被用于在 OpenSim 中生成特定于主题的全身模型。此外,它还便于在 OpenSim 框架中计算关节角度,随后可以将这些角度应用于在 MATLAB 框架中开发的特定于主题的机器人模型。该数据集包括十个健康参与者执行的九项日常活动和八项运动范围活动,每个动作的两种变化各重复两次,总共展示了所有动作的 340 次。一个全身人类运动数据库可供公众在辅助、康复和机器人技术中心(CARRT)-机器人人体上部模型运动捕捉数据中使用,其中包含.c3d 格式的原始运动数据、适用于 OpenSim 模型的.trc 格式的运动数据以及基于 MATLAB 的模型的后处理运动数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/312b/10611251/3b27b927d107/sensors-23-08354-g001.jpg

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