| Multi-robot system is a hot issue in the field of current robot research. It is the cross-prod-uct of robotics, communications technology, computer technology, control theory, electronic technology, artificial intelligence and other technical disciplines. In the multi-robot technolo-gy research, path planning technology is the core of its research, and it plays a very importa-nt role in the autonomous navigation and the achievement of complex task of the robot, so it can reflect the intelligent level of the multi-robot systems. Therefore, the path planning of the multi-robot is covered by the researchers as an important issue.Path planning is the precondition of accomplishing missions logically and efficiently for multi-robots. How to choose reasonable or even optimal path is important question for study. Multi-robots path planning works in the Multi-robot system. Its role is to program paths for every robot while ensuring no collision between robot and the environment or betw-een robots all the time.Multi-robot path planning takes the multi-robot systems as its research subject. Multi-robot path planning makes the robot fmd an optimal path to ensure that there will be no coll-ision among the robots and between the robots and obstacles in the work space. Although many algorithms have been used to solve the problem, but as the multi—robot work environ-ment has become increasingly complex, mission planning becoming more demanding, it has become a hotspot to seek abetter algorithm in the field. The study of path planning is very imporrant at the condition that the accuracy of robot hardware systems can not be im-proved in a short time. Based on collecting, collating and analyzing relevant documentations about path planning for robot, This dissertation, takes path planning as its research subject, points out the new method of path planning of the multi-robot system. The primary contents are as follows:First, Path-Planning based on evolutionary Artficial Potential Field method.we propose a path planning method called Improved Artificial Potential Field method. To solve the "collision avoidance lock" for multi-robots, we add a rotating force to the robot on the base of attracting force and repulsing force in traditional APE When the robots are too near, the three forces will make all of robots in danger turn right (or left). So this avoids their being near again. Afterwards, we carry out a simulation to test the method and prove its validity.Second, Path-Planning of the Multiple Robots.This dissertation, points out a hierarchical structure of the path planning in accordance with the complexity and dynamics of the issues, combining the global path planning and local path planning effectively, improving the genetic algorithms and artificial potential field to achieve the complex multi-robot path planning. we use GA to plan routes for all robots respective on the whole. When some robots are too near,we use LAPF to negotiate them locally. We carry out a simulation and find the mixing method is better than IAPF. Finally, we plan the future work to improve the both methods.At the end of this dissertation, the main research is summarized. It makes out the main research results, and also the problems which need to further research. |
