Enabling impedance-based physical human–multi–robot collaboration: Experiments with four torque-controlled manipulators

机器人 阻抗控制 机器人学 接触力 控制工程 人机交互 扭矩 触觉技术 计算机科学 人工智能 工程类 人机交互 模拟 物理 量子力学 热力学
作者
Niels Dehio,Joshua Smith,Dennis Leroy Wigand,Pouya Mohammadi,Michael Mistry,Jochen J. Steil
出处
期刊:The International Journal of Robotics Research [SAGE]
卷期号:41 (1): 68-84 被引量:7
标识
DOI:10.1177/02783649211053650
摘要

Robotics research into multi-robot systems so far has concentrated on implementing intelligent swarm behavior and contact-less human interaction. Studies of haptic or physical human-robot interaction, by contrast, have primarily focused on the assistance offered by a single robot. Consequently, our understanding of the physical interaction and the implicit communication through contact forces between a human and a team of multiple collaborative robots is limited. We here introduce the term Physical Human Multi-Robot Collaboration (PHMRC) to describe this more complex situation, which we consider highly relevant in future service robotics. The scenario discussed in this article covers multiple manipulators in close proximity and coupled through physical contacts. We represent this set of robots as fingers of an up-scaled agile robot hand. This perspective enables us to employ model-based grasping theory to deal with multi-contact situations. Our torque-control approach integrates dexterous multi-manipulator grasping skills, optimization of contact forces, compensation of object dynamics, and advanced impedance regulation into a coherent compliant control scheme. For this to achieve, we contribute fundamental theoretical improvements. Finally, experiments with up to four collaborative KUKA LWR IV+ manipulators performed both in simulation and real world validate the model-based control approach. As a side effect, we notice that our multi-manipulator control framework applies identically to multi-legged systems, and we execute it also on the quadruped ANYmal subject to non-coplanar contacts and human interaction.

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
2秒前
大个应助洛河三千星采纳,获得10
2秒前
阳光自信的爱党少年完成签到,获得积分20
3秒前
张会发布了新的文献求助10
3秒前
KUN完成签到,获得积分20
3秒前
桐桐应助沉静胜采纳,获得10
4秒前
myy发布了新的文献求助10
4秒前
5秒前
5秒前
6秒前
6秒前
6秒前
松林揽月发布了新的文献求助10
7秒前
如昨完成签到,获得积分10
7秒前
今后应助问问采纳,获得10
8秒前
随意发布了新的文献求助10
8秒前
舒适可乐完成签到,获得积分10
9秒前
星辰大海应助宠溺Ovo采纳,获得10
9秒前
abcd_1067完成签到,获得积分10
9秒前
诚心爆米花完成签到,获得积分10
9秒前
erdongsir发布了新的文献求助10
10秒前
10秒前
Mali完成签到,获得积分10
10秒前
11秒前
11秒前
可爱的函函应助重复使用采纳,获得30
11秒前
夹心完成签到,获得积分10
11秒前
11秒前
believe发布了新的文献求助10
12秒前
AAA完成签到 ,获得积分10
13秒前
Hw发布了新的文献求助10
13秒前
上官若男应助如昨采纳,获得10
13秒前
田様应助空耳大师采纳,获得10
14秒前
14秒前
15秒前
15秒前
冬月初七发布了新的文献求助10
16秒前
传奇3应助Elk采纳,获得10
16秒前
as发布了新的文献求助10
16秒前
科研通AI6.1应助ws233采纳,获得10
17秒前
高分求助中
Modern Epidemiology, Fourth Edition 5000
Kinesiophobia : a new view of chronic pain behavior 5000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Digital Twins of Advanced Materials Processing 2000
Propeller Design 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Handbook of pharmaceutical excipients, Ninth edition 1500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6011205
求助须知:如何正确求助?哪些是违规求助? 7559747
关于积分的说明 16136440
捐赠科研通 5157970
什么是DOI,文献DOI怎么找? 2762598
邀请新用户注册赠送积分活动 1741303
关于科研通互助平台的介绍 1633583