Abstract
Foraging theory originated in attempts to address puzzling findings that arose in ethological studies of food seeking and prey selection among animals. The potential utilization of biomimicry of social foraging strategies to develop advanced controllers and cooperative control strategies for autonomous vehicles is an emergent research topic. The activity of foraging can be focused as an optimization process. In this paper, a bacterial foraging approach for path planning of mobile robots is presented. Two cases study of static environment with obstacles are presented and evaluated. Simulation results show the performance of the bacterial foraging in different environments in the planned trajectories.
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Sierakowski, C.A., Coelho, L.d. (2006). Path Planning Optimization for Mobile Robots Based on Bacteria Colony Approach. In: Abraham, A., de Baets, B., Köppen, M., Nickolay, B. (eds) Applied Soft Computing Technologies: The Challenge of Complexity. Advances in Soft Computing, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31662-0_15
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DOI: https://doi.org/10.1007/3-540-31662-0_15
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