Citation

Xi L, Shino M. Int. J. Environ. Res. Public Health 2020; 17(15): e5502.

Copyright

(Copyright © 2020, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph17155502

PMID

32751490

Abstract

Individuals with severe physical impairments have difficulties operating electric wheelchairs (EWs), especially in situations where fine steering abilities are required. Automatic driving partly solves the problem, although excessive reliance on automatic driving is not conducive to maintaining their residual physical functions and may cause more serious diseases in the future. The objective of this study was to develop a shared control system that can be adapted to different environments by completely utilizing the operating ability of the user while maintaining the motivation of the user to drive. The operating characteristics of individuals with severe physical impairments were first analyzed to understand their difficulties when operating EWs. Subsequently, a novel reinforcement learning-based shared control method was proposed to adjust the control weight between the user and the machine to meet the requirements of fully exploiting the operating abilities of the users while assisting them when necessary. Experimental results showed that the proposed shared control system gradually adjusted the control weights between the user and the machine, providing safe operation of the EW while ensuring full use of the control signals from the user. It was also found that the shared control results were deeply affected by the types of users.

Language: en

Keywords

reinforcement learning; driving motivation; electric wheelchair; physical impairments; shared control; user-machine interaction