首页 | 本学科首页   官方微博 | 高级检索  
     

改进人工势场的手术机器人位姿规划
引用本文:郝林佳,叶灿,都书鲜,王宇,武博,张楠.改进人工势场的手术机器人位姿规划[J].控制理论与应用,2022,39(6):1121-1129.
作者姓名:郝林佳  叶灿  都书鲜  王宇  武博  张楠
作者单位:首都医科大学生物医学工程学院,首都医科大学生物医学工程学院,首都医科大学生物医学工程学院,首都医科大学生物医学工程学院,首都医科大学生物医学工程学院,首都医科大学生物医学工程学院
基金项目:国家自然科学基金项目(61672362), 北京市自然科学基金项目(4172012)资助.
摘    要:运动避障与路径规划是手术机器人自动化手术中重要的技术环节,为机器人手术提供了良好的术中安全性及准确性.本研究针对上述两关键技术,提出改进人工势场的手术机器人位姿规划算法,首先,通过对引力函数进行改进,在不求取运动学逆解的情况下,能够准确驱动机械臂到达指定位姿;接着,利用快速凸包算法将障碍物凸体化,通过Gilbert Johnson Keerthi (GJK)算法计算障碍物与机械臂连杆等效圆柱面之间的最近距离,使避障距离更加准确;然后,通过自适应步长,使机械臂运动更加平稳快速;最后,引入动态引力常数,使机械臂具有逃离局部极小值的能力.实验结果表明,本研究能够让机器人在避障情况下平稳快速到达规划位姿,并在陷入局部极小值时逃逸,为未来医疗机器人在自动化手术方面提供了新思路.

关 键 词:避障  路径规划  手术机器人  人工势场  自适应步长  局部极小值
收稿时间:2021/7/20 0:00:00
修稿时间:2022/4/24 0:00:00

Pose planning for surgical robot with improved artificial potential field method
HAO Lin-ji,YE Can,DU Shu-xian,WANG Yu,WU Bo and ZHANG Nan.Pose planning for surgical robot with improved artificial potential field method[J].Control Theory & Applications,2022,39(6):1121-1129.
Authors:HAO Lin-ji  YE Can  DU Shu-xian  WANG Yu  WU Bo and ZHANG Nan
Affiliation:School of Biomedical Engineering,Capital Medical University,School of Biomedical Engineering,Capital Medical University,School of Biomedical Engineering,Capital Medical University,School of Biomedical Engineering,Capital Medical University,School of Biomedical Engineering,Capital Medical University,School of Biomedical Engineering,Capital Medical University
Abstract:Motion obstacle avoidance and path planning are very important technical links in automated surgery of surgical robots, which provide good intraoperative safety and accuracy for robotic surgery. Aiming at the above two key technologies, a pose planning algorithm of surgical robot with improved artificial potential field is proposed. Firstly, by improving the gravitational function, the robot can be accurately driven to the specified pose without obtaining the inverse kinematics solution. Secondly, the fast convex hull algorithm is used to make the obstacle convexification, and the closest distance between the obstacle and the equivalent cylindrical surface of the links are calculated by the Gilbert Johnson Keerthi (GJK) algorithm, so that the obstacle avoidance distance is more accurate. Thirdly, the adaptive step size is adopted to make the movement of the robot more stable and faster. Finally, a dynamic gravitational constant is proposed to enable the robot to escape from the local minimum. The experimental results show that the research can make the robot smoothly and quickly reach the planned pose while avoiding obstacles, and escape when falling into the local minimum, which provides new ideas for future medical robots in automated surgery.
Keywords:obstacle avoidance  path planning  surgical robots  artificial potential field  adaptive step size  local minimum
点击此处可从《控制理论与应用》浏览原始摘要信息
点击此处可从《控制理论与应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号