A Vision-Based Human Digital Twin Modeling Approach for Adaptive Human–Robot Collaboration

人工智能 背景(考古学) 计算机科学 灵活性(工程) 人机交互 卷积神经网络 人机交互 感知 机器人 数学 生物 统计 古生物学 神经科学
作者
Junming Fan,Pai Zheng,C.K.M. Lee
出处
期刊:Journal of Manufacturing Science and Engineering-transactions of The Asme [ASME International]
卷期号:145 (12) 被引量:6
标识
DOI:10.1115/1.4062430
摘要

Abstract Human–robot collaboration (HRC) has been identified as a highly promising paradigm for human-centric smart manufacturing in the context of Industry 5.0. In order to enhance both human well-being and robotic flexibility within HRC, numerous research efforts have been dedicated to the exploration of human body perception, but many of these studies have focused only on specific facets of human recognition, lacking a holistic perspective of the human operator. A novel approach to addressing this challenge is the construction of a human digital twin (HDT), which serves as a centralized digital representation of various human data for seamless integration into the cyber-physical production system. By leveraging HDT, performance and efficiency optimization can be further achieved in an HRC system. However, the implementation of visual perception-based HDT remains underreported, particularly within the HRC realm. To this end, this study proposes an exemplary vision-based HDT model for highly dynamic HRC applications. The model mainly consists of a convolutional neural network that can simultaneously model the hierarchical human status including 3D human posture, action intention, and ergonomic risk. Then, on the basis of the constructed HDT, a robotic motion planning strategy is further introduced with the aim of adaptively optimizing the robotic motion trajectory. Further experiments and case studies are conducted in an HRC scenario to demonstrate the effectiveness of our approach.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
111111111发布了新的文献求助30
刚刚
柠檬水不要柠檬关注了科研通微信公众号
1秒前
6666完成签到,获得积分10
1秒前
加菲丰丰应助Vce April采纳,获得20
3秒前
innocence@x关注了科研通微信公众号
5秒前
Chiier发布了新的文献求助10
6秒前
6秒前
晴空之下完成签到 ,获得积分10
6秒前
7秒前
共享精神应助cola采纳,获得10
7秒前
邹葶完成签到,获得积分10
7秒前
塔图姆完成签到,获得积分10
9秒前
9秒前
草木发布了新的文献求助10
10秒前
11秒前
12秒前
梅残风暖发布了新的文献求助10
13秒前
塔图姆发布了新的文献求助10
13秒前
orixero应助木偶采纳,获得10
14秒前
wtzhang16完成签到,获得积分10
14秒前
冷艳的寻冬完成签到 ,获得积分10
16秒前
今后应助小九不太乖采纳,获得10
17秒前
17秒前
19秒前
迷路的平萱完成签到,获得积分10
20秒前
22秒前
22秒前
R喻andom发布了新的文献求助10
22秒前
innocence@x完成签到,获得积分10
25秒前
李燕君发布了新的文献求助10
25秒前
今后应助科研通管家采纳,获得10
25秒前
葡萄成熟应助科研通管家采纳,获得30
25秒前
25秒前
科研通AI2S应助科研通管家采纳,获得10
25秒前
彭于晏应助科研通管家采纳,获得10
25秒前
NexusExplorer应助科研通管家采纳,获得10
25秒前
Lucas应助科研通管家采纳,获得10
25秒前
在路上应助科研通管家采纳,获得10
25秒前
隐形曼青应助科研通管家采纳,获得10
25秒前
25秒前
高分求助中
The Oxford Handbook of Social Cognition (Second Edition, 2024) 1050
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Chen Hansheng: China’s Last Romantic Revolutionary 500
COSMETIC DERMATOLOGY & SKINCARE PRACTICE 388
Case Research: The Case Writing Process 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3141416
求助须知:如何正确求助?哪些是违规求助? 2792460
关于积分的说明 7802733
捐赠科研通 2448629
什么是DOI,文献DOI怎么找? 1302677
科研通“疑难数据库(出版商)”最低求助积分说明 626650
版权声明 601237