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Autonomous systems assume intelligent behaviour with capabilities of dealing in complex and changing environments. Problem of path planning, which can be observed as an optimization problem, seems to be of high importance for arising of intelligent behaviour for different real-world problem domains. Swarm intelligence has gained increasingly high interest among the researchers from different areas, like, science, commerce and engineering over the last few years. It is particularly suitable to apply methods inspired by swarm intelligence to various optimization problems, especially if the space to be explored is large and complex. This article presents application of Honey-bees mating algorithm (HBO) to a non linear Diophantine equation benchmark problem and comparison with results of a genetic algorithm (GA) designed for the same purpose. In second part of the work, HBO algorithm is applied to solve a problem of guidance of mobile robot through the space with differently shaped and distributed obstacles. Fuzzy fitness function for selective evaluation of paths found by the algorithm is proposed. The performance of the algorithm is comparable to genetic algorithm developed for the same purpose.

Honey-bees optimization algorithm applied to path planning problem