Abstract
This paper focuses on a planning method for an iterative transportation task by cooperative mobile robots. This task requires the generation of appropriate robot paths and the formation of groups of cooperating robots. In order to realize efficient transportation, the planning architecture consisting of “Path-Generation Phase” and “Strategy-Making Phase” is proposed. The former phase generates robot paths from global environmental information and produces a graph network from the derived robot paths. In the latter phase, every robot learns a behavior strategy based on the derived graph. An asymptotic strategy-making method is used here. The global transportation strategy derived by the proposed architecture can be divided into three types, and simulation results indicate that forming the global transportation type realizes efficient transportation. Experimental results indicate that the proposed architecture is practical enough for real situation.
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