Intelligent Systems Laboratory

Coordination and task sharing among robots are carried out by an automata in a distributed and cooperative manner. The automata assigns tasks to robots, thereby fulfilling coordination among robots. This automata is based on basic energy principle. In this work, artificial potential functions based on the partial knowledge will be developed. However, it will be necessary to adapt the artificial potential functions and formulize the problem as negative gradient system groups. The optimal point is defined using Nash equilibrium. The effect of partial and/or uncertain information receiving from sensors on the robots will be analyzed. In C.S. Karagöz's work, it is assumed that the robot has perfect knowledge of the environment. Uncertain sensory information case for one robot was investigated by H.Bayram. This assumption is usually not possible in the multi-robot. When all agents know always other agents' positions, communication problem occurs. In more realistic case, the robots have only partial or local knowledge. Using these functions, task performance of robots group will be analyzed. In the experimental stage, EDAR2G and EDAR3G will be used to evaluate the performance of the method.