M. Kulich, M. Rollo, R. Mzl, J. Chudoba, P. Benda, L. Přeučil, M. Pěchouček, and P. tepn (Czech Republic)
multi-robot exploration, task allocation, localization, plan ning, multi-agent systems
The paper deals with a problem of exploring an unknown environment by a team of mobile robots. Widely used ap proach in the robotic community is frontier based explo ration. We combine this technique with a multi-agent ar chitecture A-globe, which allows solving the exploration problem with limited communication accessibility and with changing number of participating robots. Frontier based approach heavily depends on path planning algorithm. A novel method combining A* search with harmonic poten tial fields is also presented. Finally, the Iterative Closest Point localization algorithm has been improved in several ways, in order to increase its speed and robustness. The whole exploration framework has been implemented and tested in both simulated and real environments.
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