Brain-Controlled Multi-Robot at Servo-Control Level Based on Nonlinear Model Predictive Control  

作　　者：Zhenge Yang Luzheng Bi Weiming Chi Haonan Shi Cuntai Guan 

机构地区：[1]the School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China. [2]the School of Computer Science and Engineering,Nanyang Technological University,Singapore 639673,Singapore

出　　处：《Complex System Modeling and Simulation》2022年第4期307-321,共15页复杂系统建模与仿真（英文）

基　　金：the National Natural Science Foundation of China(No.51975052).

摘　　要：Using a brain-computer interface(BCI)rather than limbs to control multiple robots(i.e.,brain-controlled multi-robots)can better assist people with disabilities in daily life than a brain-controlled single robot.For example,one person with disabilities can move by a brain-controlled wheelchair(leader robot)and simultaneously transport objects by follower robots.In this paper,we explore how to control the direction,speed,and formation of a brain-controlled multi-robot system(consisting of leader and follower robots)for the first time and propose a novel multi-robot predictive control framework(MRPCF)that can track users'control intents and ensure the safety of multiple robots.The MRPCF consists of the leader controller,follower controller,and formation planner.We build a whole brain-controlled multi-robot physical system for the first time and test the proposed system through human-in-the-loop actual experiments.The experimental results indicate that the proposed system can track users'direction,speed,and formation control intents when guaranteeing multiple robots’safety.This paper can promote the study of brain-controlled robots and multi-robot systems and provide some novel views into human-machine collaboration and integration.

关 键 词：brain-computer interface human-machine collaboration model predictive control multi-robot system 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]