Odor Source Localization Using Multiple Mobile Robots Based On Maximum Entropy

In biological world, animals use odors to exchange information, find mates, search for food，and so on. Inspired by biological, in the1990s, researchers started to utilize mobile robots withonboard odor sensor to search the position of odor source.The research on localization of unknown odor source is related to the research fields such asmathematics, mechanics, sensing and information processing, computer program, and so on. It isexpected that mobile robots will have huge practical value and play more and more important rolesin application areas like detecting toxic gas leakage, the drug inspection, disaster rescue, and so on.This thesis focuses on the problem of odor source localization using a multi-robot system. Theresearch can be concluded as follows.First, this thesis introduces ROS simulation platform, which need to be built by four steps asfollows: environment model, plume model, sensor model, localization model. Simultaneously, wesummarize the algorithms about the problem of odor source localization in the current reference.Second, on the decision level, we put forward a mobile multi-robot decision-making scheme,which is based on Shannon’s entropy theory. A discrete grid map is first used to model theobservation model. Then, the posteriori probability distribution for the position of the odor sourceon observation model is given. Finally, the Shannon’s Entropy theory for the probability distributionis employed to make the decision on the movement direction of the robot group.Third, on the control level, we give a finite-time consensus algorithm. A Lyapunov approach isused to analyze the finite-time convergence of the proposed consensus algorithm. Then, on the basisof the proposed finite-time consensus algorithm, a finite-time parallel motion control algorithm,which can control the group of robots to trace the plume and move toward the probable position ofodor source, is derived. Next, a finite-time circular motion control algorithm, which enables therobot group to circle the probable position of the odor source in order to search for odor clues, isalso developed.Finally, the results base on ROS platform are given and analyzed. Then, we summarize theproblems of the odor source localization and points out the future directions.