Intelligent multirobot systems performing cooperative tasks

We discuss how to plan the actions of a multirobot system acting in the real world by using task constraints for implicit coordination. Classifying and modelling task constraints is shown to be a very powerful mechanism for giving each robot an extended capability of coordinating itself with the other robots of the whole system. Thus, we investigate the problem of performing collective tasks with emphasis on the use of task constraints to get intelligent coordination among the individual members of the robot group. We have also introduced a set of macroscopic parameters that allow us to evaluate the evolution of the whole system. They depend on both the global task, and the environment dynamics, allowing the robots to implicitly communicate their intention to be involved in complex actions. Other group members become aware of their task simply by recognizing configuration patterns of the environment. We illustrate some examples of such a coordination taken from the scenario of both service robotics and of simulated robot games