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Discrete Genetic Algorithm for Solving Task Allocation of Multi-robot Systems

Mohadeseh Soleimanpour-Moghadam, Hossein Nezamabadi–pour

Year
2020
Citations
12

Abstract

In this paper, a Discrete Genetic Algorithm (DGA) is proposed for solving the task allocation problem in a multi-robot scenario. In the proposed DGA, a discrete population generation is proposed to adjust the genetic algorithm for solving the task allocation problem of a multi-robot system which aims to maintain the balance of exploration and exploitation. In the proposed scenario, the defined problem consists of assigning the robots to the known targets in two-dimensional search space. The scalability of the proposed DGA algorithm is tested in terms of the number of robots. The comparison confirms the superiority of the proposed method compared to the existing methods.

Keywords

RobotComputer scienceGenetic algorithmTask (project management)ScalabilityPopulationMathematical optimizationDiscrete spaceRobot kinematicsArtificial intelligence

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