Study On Path Planning Algorithm And Navigation Systems For Multiple Mobile Robots

This paper addresses path planning algorithm and navigation systems for multiple mobile Robots in multiple robots coordinated system. Global path planning combined with local path planning for robot navigation. Evolutionary dynamic programming is used in global path planning with the information of robots as dynamic weight. Artificial potential field method used in local path planning, and every robot reach the goal and avoids obstacle in the multiple mobile robots system. We use the path planning algorithm and navigation systems in the distributed multiple robots simulation system, robots works well. So we know the path planning algorithm and navigation systems are suitable for the multiple robots coordination system.We study three problems:1. Set up the navigation system for the multiple mobile robots system;2. Present the method of the path planning algorithm for the multiple mobile robots system;3. Use the path planning algorithm and navigation system in the distributed multiple robots simulation system。In the navigation system, Global path planning combined with local path planning for robot navigation. Evolutionary dynamic programming is used in global path planning with the information of robots as dynamic weight. Artificial potential field method used in local path planning, and every robot reach the goal and avoids obstacle in the multiple mobile robots system. We adopt Evolutionary dynamic programming in area path planning. The static weight of the road is the length of the road and the dynamic weight of the road is the information of the other robots in the multiple robots system. When a lot of robots in one road, robot will not plans it's path with this road. So the condition of the road will improve. The complexity of the method is O(n). So it's real good path planning method for the multiple robots system. When the robot in a cross, it will plan it's road again form it's position to the goal. Robot choices the optimal path in the map.We adopt artificial potential field method in local path planning. In artificial potential field, goal point attracts robot, obstacle repulse robot. So robot will go to the goal and avoid obstacle. The complexity of the method is O(n). So it's real good path planning method for the multiple robots system. When the robot in a cross, it will plan it's road again form it's position to the goal. Robot choices the optimal path on the map. It's important for robot in the multiple mobile robots system to avoid obstacle. Artificial potential field method satisfied the request of the multiple mobile robots system.We use the path planning algorithm and navigation systems in the distributed multiple robots simulation system.The distributed multiple robots simulation system include the module of display, server, robot, communication module. The map of environment save in server ,which communicate information with robots. Robot plans area path by evolutionary dynamic programming and local path by artificial potential field method.We experiment the path planning algorithm and navigation systems use the distributed multiple robots simulation system, include area path planning experimentation, local path planning experimentation, multiple mobile robots path planning experimentation. Through these experimentations, we know the path planning algorithm and navigation systems have the good performance using in the multiple mobile robots system.