Back to Search Start Over

Wheelchair Automatic Docking Method for Body-Separated Nursing Bed Based on Grid Map

Authors :
Yudi Zhu
Qiaoling Meng
Hongliu Yu
Haitao Wang
Jie Hu
Ping Li
Bingshan Hu
Source :
IEEE Access, Vol 9, Pp 79549-79561 (2021)
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

To improve the mode and precision of wheelchair/nursing-bed automatic docking, a novel central embedded wheelchair/nursing-bed automatic docking method based on grid map is proposed. Firstly, Laplace operator and Iterative Closest Point (ICP) algorithm are used to filter and match Lidar point cloud, and the linear features of V-shaped artificial landmark are fitted by Split-merge method and least square method. Then Extended Kalman Filter (EKF) is used to fuse Inertial Measurement Unit (IMU) and odometer data to realize the localization of the bed and wheelchair. Meanwhile, the grid map is used for path planning. Based on the center-line of the two rear wheels and the angular bisector of V-shaped artificial landmark, the wheelchair pose is adjusted in real-time to ensure that the wheelchair gradually approaches the bed along the angular bisector of V-shaped artificial landmark. The yaw angle is reduced by using the improved Proportion Integration Differentiation (PID). 9 sets of experimental data, ie. (x, y, $\theta $ ) were collected at different starting positions during the docking process. The results show that the yaw angle of the wheelchair during the docking process is controlled within 2.5°, and the distance deviation between the final position and the ideal position of the wheelchair after docking is controlled within 0.02m. In the case of light interference with different luminous fluxes, the docking can still maintain good performance. The proposed docking algorithm has the robust performance of rapid response and low steady error, which can greatly improves the self-care ability of the bedridden elderly, and reduces the labor intensity of the nursing staff.

Details

Language :
English
ISSN :
21693536
Volume :
9
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.fa0d18e6ad4259a2eef03673202401
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2021.3084620