Human-robot cooperation control based on a dynamic model of an upper limb exoskeleton for human power amplification

被引:99
作者
Lee, Hee-Don [1 ]
Lee, Byeong-Kyu [1 ]
Kim, Wan-Soo [1 ]
Han, Jung-Soo [2 ]
Shin, Kyoo-Sik [3 ]
Han, Chang-Soo [3 ]
机构
[1] Hanyang Univ, Dept Mech Engn, Seoul 133791, South Korea
[2] Hansung Univ, Dept Mech Syst Engn, Seoul, South Korea
[3] Hanyang Univ, Dept Robot Engn, Gyeonggi Do, South Korea
关键词
Upper limb exoskeleton; Human-robot cooperation control; Dynamic model based control; Power assistive robot; Physical human-robot interaction;
D O I
10.1016/j.mechatronics.2014.01.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a human-robot cooperation controller for the motion of the upper limb exoskeleton. The system permits three degrees of freedom using an electrical actuator that is mainly controlled by force sensor signals. These signals are used to generate the torque required to drive the exoskeleton. However, singularities exist when the force signals in the Cartesian coordinate system are transformed into torques in the joint coordinate system. Therefore, we apply the damped least squares method. When handling a load, torque compensation is required about its mass. Therefore, we installed a force sensor at the point of the robot's end-effector. It measures the forces between the exoskeleton and the load. Then, these forces are used to compensate within a static model for handling loads. We performed control stability and load handling experiments to verify the effectiveness of the controller. Via these, we confirmed the effectiveness of the proposed controller. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:168 / 176
页数:9
相关论文
共 20 条
[1]  
Andreasen DS, 2005, INT C REHAB ROBOT, P333
[2]  
Buss SR, 2004, INTRO INVERSE KINEMA, P1
[3]   Soft exoskeletons for upper and lower body rehabilitation - Design, control and testing [J].
Caldwell, Darwin G. ;
Tsagarakis, N. G. ;
Kousidou, Sophia ;
Costa, Nelson ;
Sarakoglou, Ioannis .
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS, 2007, 4 (03) :549-573
[4]   Real-time myoprocessors for a neural controlled powered exoskeleton arm [J].
Cavallaro, Ettore E. ;
Rosen, Jacob ;
Perry, Joel C. ;
Burns, Stephen .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2006, 53 (11) :2387-2396
[5]  
Craig J.J., 2004, Introduction to Robotics: Mechanics and Control, V3rd
[6]   OVERVIEW OF DAMPED LEAST-SQUARES METHODS FOR INVERSE KINEMATICS OF ROBOT MANIPULATORS [J].
DEO, AS ;
WALKER, ID .
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1995, 14 (01) :43-68
[7]  
Hayashibara Y, 1995, RO-MAN'95 TOKYO: 4TH IEEE INTERNATIONAL WORKSHOP ON ROBOT AND HUMAN COMMUNICATION, PROCEEDINGS, P379, DOI 10.1109/ROMAN.1995.531990
[8]   HUMAN EXTENDERS [J].
KAZEROONI, H ;
GUO, JH .
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 1993, 115 (2B) :281-290
[9]   Neuro-fuzzy control of a robotic exoskeleton with EMG signals [J].
Kiguchi, K ;
Tanaka, T ;
Fukuda, T .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2004, 12 (04) :481-490
[10]   Energy-efficient Gait Pattern Generation of the Powered Robotic Exoskeleton using DME [J].
Kim, Wansoo ;
Lee, Seunghoon ;
Kang, Minsung ;
Han, Jungsoo ;
Han, Changsoo .
IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010), 2010, :2475-2480