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.
Bio-Inspired Coalition Formation Algorithms for Multirobot Systems
Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received August 21, 2015; final manuscript received February 6, 2018; published online April 26, 2018. Assoc. Editor: Bahram Ravani.
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Qian, B., and Cheng, H. H. (April 26, 2018). "Bio-Inspired Coalition Formation Algorithms for Multirobot Systems." ASME. J. Comput. Inf. Sci. Eng. June 2018; 18(2): 021010. https://doi.org/10.1115/1.4039638
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