Team Robot Motion Planning in Dynamics Environments Using a New Hybrid Algorithm (Honey Bee Mating Optimization-Tabu List)

Abstract

This paper describes a new hybrid algorithm extracted from honey bee mating optimization (HBMO) algorithm (for robot travelling distance minimization) and tabu list technique (for obstacle avoidance) for team robot system. This algorithm was implemented in a C++ programming language on a Pentium computer and simulated on simple cylindrical robots in a simulation software. The environment in this simulation was dynamic with moving obstacles and goals. The results of simulation have shown validity and reliability of new algorithm. The outcomes of simulation have shown better performance than ACO and PSO algorithm (society, nature algorithms) with respect to two well-known metrics included, ATPD (average total path deviation) and AUTD (average uncovered target distance).