Localization of unknown odor source based on Shannon´s entropy using multiple mobile robots

This paper deals with the problem of odor source localization by designing a collective decision-making mechanism based on Shannon´s entropy and using two finite-time motion control algorithms for multiple mobile robots. Specifically, for the collective decision-making mechanism, a discrete grid map is first used to model the search environment. Then, the posteriori probability distribution for the position of the odor source on the discrete grid map is recursively updated by the detection events and non-detection events. Next, the Shannon´s entropy for the probability distribution is employed to collectively make the decision on the movement direction of the robot group. For the motion control, the finite-time parallel motion control algorithm and the finite-time circular motion control algorithm are described. Moreover, two motion control algorithms are further extended in order to enable the robot group to avoid obstacles. Finally, the effective of the collective decision-making mechanism and two finite-time motion control algorithms is illustrated for the problem of odor source localization.