Planar Multi-Robot Realizations Of Connectivity Graphs Using Genetic Algorithms
IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010)(2010)
摘要
This paper considers the problem of planar multi-robot realizations of connectivity graphs. A realization is a set of planar positions for a team of robots with a connectivity graph that is identical to an a priori given connectivity graph with the additional constraint that it must be feasible. Feasibility means that that the robots must not be overlapping with each other. As the associated mathematical problem is known to be NP-hard, a stochastic approach based on genetic algorithms is proposed. First, a population set based on randomly generated planar and feasible multi-robot positions is generated. Next, a fitness function that measures the similarity of the graph of each member is constructed. Finally, new reproduction operators that enable the evolution of generations are introduced. An extensive statistical study with different number of robots demonstrates that the proposed algorithm can be used to obtain fairly complicated network topologies.
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关键词
mobile robots,connected graph,fitness function,genetic algorithm,network topology,robot kinematics,stochastic processes,genetics,genetic algorithms,graph theory,indexes,np hard problem
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