Human-Robot Cooperative Motion Constraint Control of Surgical Robot Based on Virtual Fixture

被引:1
作者
Zhu, Jiayu [1 ]
Sun, Zhen [1 ]
Shen, Yu [1 ]
Su, Baiquan [3 ]
Qi, Yansong [2 ]
Wang, Junchen [1 ]
机构
[1] Beihang Univ, Sch Mech Engn & Automat, Beijing 100191, Peoples R China
[2] Inner Mongolia Peoples Hosp, Dept Orthoped, Sports Med Ctr, Hohhot 010017, Peoples R China
[3] Beijing Univ Posts & Telecommun, Sch Automat, Med Robot Lab, Beijing 100876, Peoples R China
来源
2022 WRC SYMPOSIUM ON ADVANCED ROBOTICS AND AUTOMATION, WRC SARA | 2022年
关键词
D O I
10.1109/WRCSARA57040.2022.9903968
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Surgical robot is one of the most important application fields of human-robot collaboration. Since the operating objects are often fragile human tissues, how to improve the safety of the surgical process is the key for practical application of surgical robots. General human-robot interaction methods for safety such as collision detection and obstacle avoidance are relatively passive and robot-based, having difficulty in dealing with complex surgical scenarios. Virtual Fixture(VF), an active motion constraint method, is more suitable for shared control in surgical scenarios. This paper introduces a combination of VF method with admittance control for avoiding damage to robot or tissues while complying with doctor's intention. Firstly, in order to obtain the human-robot interaction force, a statistical method for six-dimensional force sensor calibration is proposed. Then, two velocity-based admittance control models are compared by simulation, and the first order inertial model is selected. On the basis of these, a variety of hard VFs with visual information are established. Finally, the effectiveness of the proposed method and the causes of violation are analyzed by experiments on a serial robot manipulator.
引用
收藏
页码:64 / 70
页数:7
相关论文
共 19 条
[1]  
Abbott JJ, 2007, SPRINGER TRAC ADV RO, V28, P49
[2]  
[Anonymous], 2007, Practical Optimization: Algorithms and Engineering Applications
[3]   Vision-assisted control for manipulation using virtual fixtures [J].
Bettini, A ;
Marayong, P ;
Lang, S ;
Okamura, AM ;
Hager, GD .
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 2004, 20 (06) :953-966
[4]   Active Constraints/Virtual Fixtures: A Survey [J].
Bowyer, Stuart A. ;
Davies, Brian L. ;
Rodriguez y Baena, Ferdinando .
IEEE TRANSACTIONS ON ROBOTICS, 2014, 30 (01) :138-157
[5]   A Review of Algorithms for Compliant Control of Stiff and Fixed-Compliance Robots [J].
Calanca, Andrea ;
Muradore, Riccardo ;
Fiorini, Paolo .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2016, 21 (02) :613-624
[6]   Measurement and modeling of McKibben pneumatic artificial muscles [J].
Chou, CP ;
Hannaford, B .
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 1996, 12 (01) :90-102
[7]  
Chu A, 2005, IEEE INT CONF ROBOT, P4345
[8]  
Daerden Frank, 2002, European Journal of Mechanical and Environmental Engineering, V47, P11
[9]  
DEFAZIO TL, 1984, IND ROBOT, V11, P238
[10]   Virtual-Fixture Based Drilling Control for Robot-Assisted Craniotomy: Learning From Demonstration [J].
Duan, Xingguang ;
Tian, Huanyu ;
Li, Changsheng ;
Han, Zhe ;
Cui, Tengfei ;
Shi, Qingxin ;
Wen, Hao ;
Wang, Jin .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (02) :2327-2334