'Yuragi'-Based Adaptive Mobile Robot Search With and Without Gradient Sensing: From Bacterial Chemotaxis to a Levy Walk

Abstract

Many biologically inspired approaches have been investigated in relation to research on mobile robot(s) that can effectively locate targets that induce gradient information. Here, we concentrate on realizing an adaptive searching behavior in a mobile robot that is simple, yet effective with and without sensing the gradient information. We are interested in two searching behaviors found in biological creatures: bacterial chemotaxis (probably the simplest yet effective gradient sources searching behavior found in living creatures) and Levy walk (a specialized random walk with fractal movement trajectories that optimize random search for sparsely and randomly distributed target(s)). Our approach is to propose a unifying framework based on 'yuragi' (biological fluctuation) to implement and combine the two searching behaviors.