Abstract
In this paper, three random search strategies are implemented and compared in odour finding using multiple robots. The first strategy is Brownian walk (BW). As a typical uncorrelated random search strategy, BW combines a Gaussian distribution of move length with a uniform distribution of turning angles. Another two strategies are correlated random search strategies, namely correlated random walk (CRW) and Levy walk (LW). CRW and LW are obtained by replacing the distribution of move lengths and turning angles in BW with wrapped Cauchy distribution and Levy distribution, respectively. Experiments with the three random search strategies were conducted using four MrCollie robots in our laboratory. Results show that the two correlated random search strategies (i.e., CRW and LW) are more time-efficient than BW, and that LW obtains higher time-efficiency than CRW with respect to our experimental setup.
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