| Literature DB >> 35582266 |
Yingbai Hu1,2, Jian Li3, Yongquan Chen3,1, Qiwen Wang3,1, Chuliang Chi3,1, Heng Zhang3,1, Qing Gao3,1, Yuanmin Lan1,4, Zheng Li1,5, Zonggao Mu1,6, Zhenglong Sun3,1, Alois Knoll2.
Abstract
The outbreak of novel coronavirus pneumonia (COVID-19) has caused mortality and morbidity worldwide. Oropharyngeal-swab (OP-swab) sampling is widely used for the diagnosis of COVID-19 in the world. To avoid the clinical staff from being affected by the virus, we developed a 9-degree-of-freedom (DOF) rigid-flexible coupling (RFC) robot to assist the COVID-19 OP-swab sampling. This robot is composed of a visual system, UR5 robot arm, micro-pneumatic actuator and force-sensing system. The robot is expected to reduce risk and free up the clinical staff from the long-term repetitive sampling work. Compared with a rigid sampling robot, the developed force-sensing RFC robot can facilitate OP-swab sampling procedures in a safer and softer way. In addition, a varying-parameter zeroing neural network-based optimization method is also proposed for motion planning of the 9-DOF redundant manipulator. The developed robot system is validated by OP-swab sampling on both oral cavity phantoms and volunteers.Entities:
Keywords: Deep learning for visual perception; medical robots and systems; redundant robots; task and motion planning
Year: 2021 PMID： 35582266 PMCID： PMC8905611 DOI： 10.1109/LRA.2021.3062336
Source DB: PubMed Journal: IEEE Robot Autom Lett