【摘要】 随着机器人工作环境越来越复杂,通过对其示范性的教学,可以使机器人更快地适应所处的环境,更好地完成人类所给的任务。在机器人行为中,机械臂在机器人工作中是不可缺少的。近年来,对机械臂抓取行为的建模控制成为科研工作的一个热点。最前沿的方法多从行为获取和行为表征2个方面着手,在行为获取方面大致有2种方法,一种是真人示教法,另一种是虚拟平台示教法;行为表征方面多采用深度学习的方法。本文从数据获取的角度对近几年机械臂建模和控制的研究发展进行综述。更多还原

【Abstract】 As the robot’s working environment becomes more and more complex,through exemplary teaching to them,we can make the robot adapt to its environment faster and better accomplish the missions that humans have given. In the robot’s behavior,the robot arm is indispensable in the robot’s work. In recent years,the modeling and control of robotic arm grabbing has become a hot topic in scientific research. The most cutting-edge methods start with behavior acquisition and behavioral representation. There are roughly two methods for behavior acquisition,one is the real-person teaching method,the other is the virtual platform teaching method,and most of the behavioral characterization uses deep learning method. In this paper,the method of data acquisition is used as an example to review the research and development of manipulator modeling and control in recent years.更多还原