Intelligence evolution for service robot: An ADRC perspective

• Published in: Control theory and technology Vol. 16; no. 4; pp. 324 - 335
• Main Authors: Xiang, Guofei, Huang, Yao, Yu, Jingrui, Zhu, Mingde, Su, Jianbo
• Format: Journal Article
• Language: English
• Published: Guangzhou South China University of Technology and Academy of Mathematics and Systems Science, CAS 01-11-2018; Springer Nature B.V; Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
• Subjects: Active control; Complexity; Computational Intelligence; Control; Control and Systems Theory; Engineering; Evolution; Human engineering; Intelligence; Mechatronics; Optimization; Robotics; Robots; Service robots; Systems Theory; Visual control; motion control; nonholonomic constraints; visual servoing; active disturbance rejection control (ADRC); eye-hand-torque coordination; simultaneous localization and mapping (SLAM); Service robot; human-robot interaction (HMI)
• ISSN: 2095-6983; 2198-0942
• DOI: 10.1007/s11768-018-8073-6

The strategy of active disturbance rejection control (ADRC) and its applications in intelligence evolution for service robot are summarized. It is also shown that the philosophy of ADRC is consistent with the essential characteristics of intelligence evolution. Most importantly, we concentrate on five core issues which will be encountered when applying ADRC to deal with intelligence evolution for service robot, that is, how to eliminate the impact of unknown composite disturbances, how to handle the nonholonomic constraints in uncalibrated visual servoing, how to realize eye-hand-torque coordination, how to deal with the disturbance in simultaneous localization and mapping (SLAM), and how to reject the imperfections induced by network in human-robot interaction. The main purpose of this paper is to clarify the challenges encountered on intelligence evolution for service robot when one applies ADRC to, hoping that more and more researchers can give some suggestions or work together to deal with these problems, and flourishing results of ADRC from both theory and applications.