Design and Visual Servoing Control of a Hybrid Dual-Segment Flexible Neurosurgical Robot for Intraventricular Biopsy

Autor:	Chen, Jian, Chen, Mingcong, Zhao, Qingxiang, Wang, Shuai, Wang, Yihe, Xiao, Ying, Hu, Jian, Chan, Danny Tat Ming, Yeung, Kam Tong Leo, Chan, David Yuen Chung, Liu, Hongbin
Rok vydání:	2024
Předmět:	Computer Science - Robotics Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	Traditional rigid endoscopes have challenges in flexibly treating tumors located deep in the brain, and low operability and fixed viewing angles limit its development. This study introduces a novel dual-segment flexible robotic endoscope MicroNeuro, designed to perform biopsies with dexterous surgical manipulation deep in the brain. Taking into account the uncertainty of the control model, an image-based visual servoing with online robot Jacobian estimation has been implemented to enhance motion accuracy. Furthermore, the application of model predictive control with constraints significantly bolsters the flexible robot's ability to adaptively track mobile objects and resist external interference. Experimental results underscore that the proposed control system enhances motion stability and precision. Phantom testing substantiates its considerable potential for deployment in neurosurgery. Comment: Accepted by IEEE International Conference on Robotics and Automation (ICRA) 2024, 7 pages, 9 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.09679 Zobrazit plný text záznamu View this record from Arxiv