Model Predictive Control for Human Following Rehabilitation Robot

被引：0

作者：

Yan, Shihao ^{[1
]}

Tao, Jing ^{[3
]}

Huang, Jian ^{[1
,2
]}

Xue, Anshun ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Key Lab, Minist Educ Image Proc & Intelligent Control, Wuhan 430074, Peoples R China

[2] Beijing Adv Innovat Ctr Intelligent Robots & Syst, Beijing 100081, Peoples R China

[3] Minist Civil Affairs, Peoples Republ China Natl Res Ctr Rehabil Tech Ai, Beijing 100176, Peoples R China

来源：

2019 IEEE INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND ITS SOCIAL IMPACTS (ARSO) | 2019年

关键词：

Model Predictive Control; Human Following Side-by-side; Nonholonomic Mobile Robot; Rehabilitation Robot; Trajectory Tracking; MOBILE ROBOTS; TRACKING; EXOSKELETON; DESIGN;

D O I：

10.1109/arso46408.2019.8948803

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new type of rehabilitation robot that can follow the user side-by-side is designed for aiding the elderly and disabled. The Human Following Rehabilitation Robot (HFRR) consists of a metal armrest, a set of sensors and a differential mobile base. By predicting the user's speed in the future through the user's current walking speed and the preset path, the problem of human following side-by-side is converted to a problem of keeping a certain lateral distance from the predicted trajectory. Linearizing the tracking error model, the nonholonomic mobile robot (NMR) can maintain a certain lateral distance from the trajectory by using Model Predictive Control (MPC) and then follow the user side-by-side. The simulation and experimental results show the proposed controller can obtain good performance in this problem.

引用

页码：369 / 374

页数：6

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