An adaptive switching behavior between levy and Brownian random search in a mobile robot based on biological fluctuation

Biological creatures, some of them are very simple, seem to perform efficient search strategy. Recent researches show that noise in their internal mechanism may have an important role to manage this behavior. This paper focuses on realizing a simple, noise utilizing, mathematical framework that enables a mobile robot to perform random search adaptively and efficiently under changing target density. Our approach is to model and implement bacterial movement based on a recent perspective of noise utilizing mechanism in living beings: biological fluctuation. As a result, the robot will adaptively switch its random search pattern between Levy walk and Brownian walk to increase the search efficiency in a patchy environment where the target density naturally alternates.