摘要
手是人类在长期进化过程中形成的最完美的工具,能够灵活、精细的进行抓取物体等操作;机械手设计初衷是取代人手完成工作,是机器人系统的重要组成部分,因此抓取物体等操作一直是仿人机械手的研究重点;传统的抓取方法是利用机械手三指形成力封闭完成任务;但由于机械手本身结构复杂等原因,易出现控制信号偏差或某自由度未达到要求水平,使得抓取过程中目标物体脱落等问题;为了使机械手达到稳定抓取的效果,本文提出了一种效仿人手抓取的五指力封闭抓取算法,其本质是利用冗余机制解决传统三指抓取过程中可能出现的抓取不平稳或脱落的问题;首先,基于三指力平衡算法的思想上提出了满足五指力封闭抓取算法的条件;然后,对五指力封闭抓取算法进行了充分性和必要性的证明;最后,通过仿真环境下的实验抓取不同目标物体,验证了五指力封闭算法的可行性及必要性。
The hand is the most perfect tool in the human’s long-term evolution process.It can flexibly and finely perform operations,such as grabbing objects.The original intention of the manipulator,which is an important part of the robot system,is to replace the manpower.Therefore,the operation of grasping objects has always been the research focus of the humanoid manipulator.The traditional method of grasping is to use the three-finger forming force of the robot to fulfil the task.However,due to the complicated structure of the manipulator itself,it is possible that the control signal deviation or the degree of freedom does not reach the required level.As a result,these problems will cause the target object falling off during the grabbing process.In order to achieve the effect of stable grabbing,this paper proposes a five-finger closed-grabbing algorithm,which emulates human hand grabbing.The essence of this method is to use the redundancy mechanism to solve the unsuccessful crawling and falling off problems that may occur in the traditional three-finger grabbing process.Firstly,based on the idea of the three-finger force balance algorithm,the conditions for satisfying the five-finger force closed capture algorithm are proposed.Secondly,the proof of sufficiency and necessity of the five-finger closed-grabbing algorithm are provided.Finally,the feasibility and necessity of the five-finger force closure algorithm are verified by experiment,which is in the simulation environment to capture different target objects.
作者
于建均
安硕
阮晓钢
于乃功
张子豪
Yu Jianjun;An Shuo;Ruan Xiaogang;Yu Naigong;Zhang Zihao(College of Electronic and Control Engineering,Beijing University of Technology, Beijing100124, China;Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing100124, China)
出处
《计算机测量与控制》
2019年第5期192-198,共7页
Computer Measurement &Control
基金
国家自然科学基金项目(61773027)
北京市教育委员会科技计划重点项目(KZ201610005010)