Bat Algorithm for Coordinated Exploration in Swarm Robotics
Bat algorithm is a powerful bio-inspired swarm intelligence method with remarkable applications in several industrial and scientific domains. However, to the best of authors’ knowledge, this algorithm has not been applied so far to the exciting field of s
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Faculty of Sciences, University of Cantabria, Avenida de los Castros s/n, 39005 Santander, Spain 2 Department of Information Science, Faculty of Sciences, Toho University, Narashino Campus, 2-2-1 Miyama, Funabashi 274-8510, Japan 3 Department of Applied Mathematics and Computational Sciences, University of Cantabria, Avenida de los Castros s/n, 39005 Santander, Spain [email protected] http://personales.unican.es/iglesias
Abstract. Bat algorithm is a powerful bio-inspired swarm intelligence method with remarkable applications in several industrial and scientific domains. However, to the best of authors’ knowledge, this algorithm has not been applied so far to the exciting field of swarm robotics. This paper describes the first physical and computational implementation of the bat algorithm to a swarm of simple robotic units. The swarm consists of a set of identical wheeled robots equipped with simple yet powerful components that replicate the most important features of the bat algorithm by either hardware or software. The swarm has been applied to the problem of coordinated exploration, where the individual self-organizing robots generate an intelligent collective behavior emerging from the interactions between the robots and with the environment. A computational and real-world experiment has been carried out to check the feasibility and performance of this approach. Our experimental results show that the bat algorithm is extremely well suited for this task, actually leading to surprisingly intelligent behavioral patterns much better than expected. Keywords: Swarm computation · Swarm robotics exploration · Bat algorithm · Collective behavior
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Introduction Swarm Intelligence
One of the most exciting advances in artificial intelligence during the last decades is the emergence of sophisticate behaviors arising from a collection of simple, unsophisticated agents collaborating together to solve a complex problem. This field, globally known as swarm intelligence, is overcoming the traditional mathematical approaches for solving optimization problems and laying the foundations c Springer Nature Singapore Pte Ltd. 2017 J. Del Ser (ed.), Harmony Search Algorithm, Advances in Intelligent Systems and Computing 514, DOI 10.1007/978-981-10-3728-3 14
Bat Algorithm for Coordinated Exploration in Swarm Robotics
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for a new computational paradigm: the swarm computation. Under this new paradigm, there is no a centralized intelligence controlling the swarm, taking decisions, and sending orders to the swarm units about how to behave. Instead, the limited intelligence of swarm units is amplified by their (local or global) interactions. Members of the swarm have the ability to communicate with each other and with the environment, thus enhancing the global intelligence of the swarm. The interested reader is referred to [2,9] for a comprehensive overview about the field of swarm intelligence, its history, main techniques, and applications. Nowadays, swarm intelligence is attracting increasing attention owing to its
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