Research On Dynamic Team Formation For Multirobots Based On Reinforcement Learning

The content elaborated in the thesis is the technique of multirobots' team formation in the field with obstacles. The following aspects are investigated and discussed.Firstly it is the study of the architecture structure of the multirobots' cooperation. The system combines the advantage of the central and the dispersed architecture and uses the distributed architecture. With this multi-layer control , the task of every part is clear. And it is also a multi-level architecture, having three levels from above to the below.Then the detailed study of each level is illustrated here. The first level is the task planning level. In order to save the time and the memory, the method of potential and the grid is used to solve the global path planning problem. The second level is the planning of the robot's behavior. Here the thought of the Brooks behavior is used to cut the team formation into several behaviors. And the way to choose the adapted behavior in different environment is mainly the Reinforcement Learning, hi the Reinforcement Learning algorithm is explained here , the inside reinforcement signals and outside reinforcement signals are applied to show the interests of the robot and its whole group. Using this way ,the self-adaptivity ,self-determination and the cooperation of the robots are all embodied clearly. The last level is the action planning, with the fuzzy way choosing the different action.hi the simulation of the experiment , the feasibility of the technology is verified further.