Research On The Cooperation Of Multi-Robot System Under Dynamic Competitive Environments

The Cooperation is the key research problem of MRS (multi-robot system),which is that robots are organized by some rules to work together for thosetasks that cannot be completed by one single robot. The organization rulesform the architecture of MRS under which the tasks are decomposed intosubtasks and allocated to robots. So, how to construct architecture and how toallocate subtasks among robots are two difficulties must be solved forcooperation. The effective and exact opponent's intention recognition isnecessary for MRS under dynamic environments to get predominance in acompetition. The real time reactive of robots depends on intentionrecognition.Architecture, task allocation and intention recognition are the problems thatthis paper tries to resolve by Dynamic Coalition method based on opponent'sintention recognition for MRS. This method consists of three parts ininterdependent relations. The first is an architecture named dynamic coalitionstructure for robots organization, the second is gift value algorithm for tasksallocation while the third is quadratic estimation algorithm for opponent'sintention recognition.Dynamic coalition structure is a profit-drive MRS architecture, which isglobal distributed while local weakly centralized. It can give optimal solutionof tasks as possible as centralized architecture because of local weaklycentralized coalition while get over the latter's limitation of fault tolerance. Itadopts excellent robust performance of distributed architecture but presentsmuch more optimal tasks solving ability. It makes use of profit-drivemechanism like market model but avoids complex computation.Different from other common negotiation methods based on CNP, gift valuealgorithm for tasks allocation in this paper is two steps artifice. Firstly,estimate the task executing capabilities of all relative robots by gift value andselect the one who gives max value. Then, one to one negotiation happensbetween this robot and another robot, which is responsible for task allocation.The optimal solution of task allocation for different global objective can beobtained by adjusting weight vector for different estimating criterions in giftset.Quadratic estimation algorithm for intention recognition is also a two-stepartifice. The first step is to estimate the opponent's behavior series and formsits current behavior. The next step is to recognize the opponents intentionfrom its behavior series gained in previous step. This algorithm overcomestwo difficulties. One is none-real time arising from waiting the totalinformation about opponent's behaviors;the other is inaccurate arising fromrecognition by only single behavior.Import the opponents' intention results in quadratic estimation algorithm, thenrevise task set to be executed in four layers, the reactivity of MRS toenvironments can be obtained. This is the work of dynamic coalitionarchitecture based on intention recognition.Finally, those methods have been applied and validated in robot soccercompetitions as described in the last chapter.