The path towards contact-based physical human-robot interaction

被引:4
作者
Farajtabar, Mohammad [1 ]
Charbonneau, Marie [1 ]
机构
[1] Univ Calgary, Dept Mech & Mfg Engn, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada
基金
欧盟地平线“2020”;
关键词
Physical human-robot interaction; Robot safety; Robot sensing systems; Robot learning; Motion planning; Compliant control; Robot ethics; VARIABLE ADMITTANCE CONTROL; FORCE ESTIMATION; IMPEDANCE CONTROL; INDUSTRIAL ROBOT; ARTIFICIAL SKIN; HUMAN INTENTION; DIRECT-DRIVE; SAFETY; MOTION; MANIPULATION;
D O I
10.1016/j.robot.2024.104829
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the advancements in human-robot interaction (HRI), robots are now capable of operating inclose proximity and engaging in physical interactions with humans (pHRI). Likewise, contact-based pHRI is becoming increasingly common as robots are equipped with a range of sensors to perceive human motions. Despite the presence of surveys exploring various aspects of HRI and pHRI, there is presently a gap in comprehensive studies that collect, organize and relate developments across all aspects of contact-based pHRI. It has become challenging to gain a comprehensive understanding of the current state of the field, thoroughly analyze the aspects that have been covered, and identify areas needing further attention. Hence, the present survey. While it includes key developments in pHRI, a particular focus is placed on contact-based interaction, which has numerous applications in industrial, rehabilitation and medical robotics. Across the literature, a common denominator is the importance to establish a safe, compliant and human intention-oriented interaction. This endeavour encompasses aspects of perception, planning and control, and how they work together to enhance safety and reliability. Notably, the survey highlights the application of data-driven techniques: backed by a growing body of literature demonstrating their effectiveness, approaches like reinforcement learning and learning from demonstration have become key to improving robot perception and decision-making within complex and uncertain pHRI scenarios. This survey also stresses how little attention has yet been dedicated to ethical considerations surrounding pHRI, including the development of contact-based pHRI systems that are appropriate for people and society. As the field is yet in its early stage, these observations may help guide future developments and steer research towards the responsible integration of physically interactive robots into workplaces, public spaces, and elements of private life.
引用
收藏
页数:20
相关论文
共 264 条
[1]  
Admoni H, 2017, J HUM-ROBOT INTERACT, V6, P25, DOI 10.5898/JHRI.6.1.Admoni
[2]  
Agravante DJ, 2014, IEEE INT CONF ROBOT, P607, DOI 10.1109/ICRA.2014.6906917
[3]   Exploring Factors Affecting User Trust Across Different Human-Robot Interaction Settings and Cultures [J].
Ahmad, Muneeb Imtiaz ;
Alzahrani, Abdullah ;
Robinson, Simon .
PROCEEDINGS OF THE 10TH CONFERENCE ON HUMAN-AGENT INTERACTION, HAI 2022, 2022, :123-131
[4]   Do you feel safe with your robot? Factors influencing perceived safety in human-robot interaction based on subjective and objective measures [J].
Akalin, Neziha ;
Kristoffersson, Annica ;
Loutfi, Amy .
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 2022, 158
[5]   Reinforcement Learning Approaches in Social Robotics [J].
Akalin, Neziha ;
Loutfi, Amy .
SENSORS, 2021, 21 (04) :1-37
[6]  
Akgun B, 2012, ACMIEEE INT CONF HUM, P391
[7]   Improving human robot collaboration through Force/Torque based learning for object manipulation [J].
Al-Yacoub, A. ;
Zhao, Y. C. ;
Eaton, W. ;
Goh, Y. M. ;
Lohse, N. .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2021, 69
[8]   Pressure distribution classification and segmentation of human hands in contact with the robot body [J].
Albini, Alessandro ;
Cannata, Giorgio .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2020, 39 (06) :668-687
[9]  
Albus J.S., 1995, P AAAI 1995 SPRING S
[10]   A Mixed-Perception Approach for Safe Human-Robot Collaboration in Industrial Automation [J].
Amin, Fatemeh Mohammadi ;
Rezayati, Maryam ;
van de Venn, Hans Wernher ;
Karimpour, Hossein .
SENSORS, 2020, 20 (21) :1-20