Abstract
Swarms of mobile robots can be tasked with searching a geographic region for targets of interest, such as buried land mines. We assume that the individual robots are equipped with sensors tuned to the targets of interest, that these sensors have limited range, and that the robots can communicate with one anotlier to enable cooperation. I low can a swarnl of cooperating sensate robots efficiently search a given geographic region for targets in the absence of a priori information about the targets' locations? Many of the “obvious” approaches are inefficient or lack robustness. One efficient approach is to have the robots traverse a space filling curve. For many geographic search applications, this method is energy-frugal, highly robust, and provides guaranteed coverage in a finite time that decreases as the reciprocal of the number of robots sharing the search task. Furthermore, control is inherently decentralized and requires very little robot-to-robot communication for the robots to organize their movements. This report presents some preliminary results from applying the Hilbert space-filling curve to geographic search by mobile robots.
Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE-AC04 94AL85000.
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Spires, S.V., Goldsmith, S.Y. (1998). Exhaustive geographic search with mobile robots along space-filling curves. In: Drogoul, A., Tambe, M., Fukuda, T. (eds) Collective Robotics. CRW 1998. Lecture Notes in Computer Science, vol 1456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033369
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DOI: https://doi.org/10.1007/BFb0033369
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