The Cooperation And The Motion Planning Of Multi-Robot System

As a important part in the Robotic, the study of the mobile robot is also the focus of the development of the robot application. In this thesis, the cooperation and the motion planning of multi-robot system is studied. Through the analysis of a real case, the problem of the cooperation and the motion planning of multi-robot system has been divided into two parts: the upper level is action-selection and the elementary level is motion planning.. The main results of these studies are followings:1. All the questions concerning the cooperation ways of the multiple mobile robots and the main problem about real-time motion planning in the dynamic environment has been fully studied. Base on a practice case, a kind of stratified planning method has been proposed to deal with the problems of the complicated multiple robot system.2. In the upper action-selection level, the accurate prediction about the next action has been gave out base on the segmented recursive least square algorithm, witch ensure the result of the motion planning be of high efficient. A hybrid action selector witch is a integration of BP network and production system is presented to deal with the cooperation of the multiple mobile robot system. It effectively integrates the merit of the two methods and makes the process of the planning more efficiently.3. To solve the problem of the motion planning, a kind of improved artificial potential field method applied in the dynamic environment is proposed. The method mainly improve two aspects of the traditional artificial potential field method: Using the potential field intensity-based method replace the vector confusion method; Combining the motion information into the repulsive force function, which transform the static artificial field function to the dynamic artificial field function. Using this method, moving obstacle avoidance can be performed more efficiently.Simulation show the feasibility and effectiveness of the approaches and algorithms .