TY - GEN
T1 - The application of navigation technology for the medical assistive devices based on Aruco recognition technology
AU - Tian, Weihan
AU - Chen, Diansheng
AU - Yang, Zihao
AU - Yin, Hu
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/24
Y1 - 2020/10/24
N2 - In order to improve the convenience of operation for the medical assistive devices and reduce the use and maintenance cost, the Aruco recognition technology is applied to the navigation and positioning of visual guided electric assistive devices. Firstly, the differential control kinematic model of the electric wheelchair is analyzed. We discuss the feasibility of Aruco recognition technology in the application of medical assistive devices. The camera on wheelchair captures the Aruco marker data and transmits it to controller. The controller calculates the position and posture information of electric wheelchair, which provides reference for the next movement of electric wheelchair. Combining with the kinematic model of electric wheelchair, this method can realize the navigation and positioning of electric wheelchair. Experiments show that the vision guidance of Electric Wheelchair based on Aruco recognition is accurate, stable, low cost, and can be flexibly applied to the auxiliary equipment of medical institutions.
AB - In order to improve the convenience of operation for the medical assistive devices and reduce the use and maintenance cost, the Aruco recognition technology is applied to the navigation and positioning of visual guided electric assistive devices. Firstly, the differential control kinematic model of the electric wheelchair is analyzed. We discuss the feasibility of Aruco recognition technology in the application of medical assistive devices. The camera on wheelchair captures the Aruco marker data and transmits it to controller. The controller calculates the position and posture information of electric wheelchair, which provides reference for the next movement of electric wheelchair. Combining with the kinematic model of electric wheelchair, this method can realize the navigation and positioning of electric wheelchair. Experiments show that the vision guidance of Electric Wheelchair based on Aruco recognition is accurate, stable, low cost, and can be flexibly applied to the auxiliary equipment of medical institutions.
UR - https://www.scopus.com/pages/publications/85102403373
U2 - 10.1109/IROS45743.2020.9341231
DO - 10.1109/IROS45743.2020.9341231
M3 - 会议稿件
AN - SCOPUS:85102403373
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2894
EP - 2899
BT - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
Y2 - 24 October 2020 through 24 January 2021
ER -