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Bio-Inspired Coalition Formation Algorithms for Multirobot Systems

Binsen Qian, Harry H. Cheng

Year
2018
Citations
12

Abstract

This paper presents two bio-inspired algorithms for coalition formation of multiple modular robot systems. An effective and efficient coalition formation system can help modular robot system take full advantage of reconfigurability of modular robots. In this paper, the multirobot coalition formation problem is illustrated and a mathematical model for the problem is described. Two bio-inspired algorithms, ant-colony algorithm (ACA) and genetic algorithm (GA), are introduced for solving the mathematical model. With the two algorithms, it is able to form a large number of robots into many different groups for a variety of applications, such as parallel performance of multiple tasks by multiple teams of robots. The paper compares the efficiency and effectiveness of two algorithms for solving the presented problem with case study. The results for the comparison study are analyzed and discussed. Also, the implementation details of the simulation and experiment using ACA are presented in the paper.

Keywords

ReconfigurabilityModular designRobotComputer scienceAnt colony optimization algorithmsGenetic algorithmSelf-reconfiguring modular robotVariety (cybernetics)AlgorithmMathematical optimization

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