Journal
IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS
Volume 4, Issue 1, Pages 106-117Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMRB.2022.3146621
Keywords
Hybrid motion mapping; COVID-19; healthcare 4.0; medical assistive robot; HCPS
Categories
Funding
- National Natural Science Foundation of China [51975513, 51890884]
- Natural Science Foundation of Zhejiang Province [LR20E050003]
- Major Research Plan of Ningbo Innovation [2020Z022]
- Zhejiang University Special Scientific Research Fund for COVID-19 Prevention and Control [2020XGZX017]
- China Scholarship Council
- Swedish Foundation for Strategic Research (SSF) [APR20-0023]
Ask authors/readers for more resources
This paper presents a novel motion synchronization method using a hybrid mapping technique of hand gesture and upper-limb motion for teleoperation of medical assistive robots. The proposed method reduces the burden on healthcare workers, simplifies the operation, and achieves superior performance compared to traditional methods.
Driven by the demand to largely mitigate nosocomial infection problems in combating the coronavirus disease 2019 (COVID-19) pandemic, the trend of developing technologies for teleoperation of medical assistive robots is emerging. However, traditional teleoperation of robots requires professional training and sophisticated manipulation, imposing a burden on healthcare workers, taking a long time to deploy, and conflicting the urgent demand for a timely and effective response to the pandemic. This paper presents a novel motion synchronization method enabled by the hybrid mapping technique of hand gesture and upper-limb motion (GuLiM). It tackles a limitation that the existing motion mapping scheme has to be customized according to the kinematic configuration of operators. The operator awakes the robot from any initial pose state without extra calibration procedure, thereby reducing operational complexity and relieving unnecessary pre-training, making it user-friendly for healthcare workers to master teleoperation skills. Experimenting with robotic grasping tasks verifies the outperformance of the proposed GuLiM method compared with the traditional direct mapping method. Moreover, a field investigation of GuLiM illustrates its potential for the teleoperation of medical assistive robots in the isolation ward as the Second Body of healthcare workers for telehealthcare, avoiding exposure of healthcare workers to the COVID-19.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available