Learning autonomous behaviours for the body of a flexible surgical robot

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• 作者：Danilo Bruno ; Sylvain Calinon ; Darwin G. Caldwell
• 关键词：Learning from demonstrations ; Surgical robotics ; Online learning ; Nullspace control
• 刊名：Autonomous Robots
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：41
• 期：2
• 页码：333-347
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Robotics and Automation; Artificial Intelligence (incl. Robotics); Computer Imaging, Vision, Pattern Recognition and Graphics; Control, Robotics, Mechatronics;
• 出版者：Springer US
• ISSN：1573-7527
• 卷排序：41

文摘

This paper presents a novel strategy to learn a positional controller for the body of a flexible surgical manipulator used for minimally invasive surgery. The manipulator is developed within the STIFF-FLOP European project and is targeted for a laparoscopic use in remote areas of the abdominal region that are not easily accessible by means of currently available rigid tools. While the surgeon controls the end-effector during the task, the flexible body of the manipulator needs to be displaced to enter inside constrained spaces by efficiently exploiting its flexibility, without touching vital organs and structures. The proposed algorithm exploits the instruments of machine learning within the programming by demonstrations paradigm to produce a statistical model of the natural movements of the surgeon during the task. The gathered information is then reused to determine a controller in the null space of the robot that does not interfere with the surgeon task and displaces the robot body within the available space in a fully automated manner.