Swarm robotics – a case study: bat robotics

Abstract Swarm robotics is a very attractive field of research, based on applying the paradigms and methodologies of swarm intelligence to groups of simple homogeneous robots, coordinated in a distributed and decentralized way, to perform difficult tasks unreachable for individual robots. The field is motivated by the striking behavior of social insects and other swarms in nature, which are able to achieve complex tasks using only local communication and sensing capabilities. In this chapter, an overview of swarm robotics is given, describing the main features of robotic swarms and comparing them with single sophisticated robots and multirobot systems. The chapter also explores the connections of swarm robotics with swarm intelligence, and how computational swarm intelligence techniques find their roots in the intelligent behavioral patterns commonly found in many swarms in nature, from colonies of social insects to flocks of birds, fish schooling, animal herding, and many others. The chapter also summarizes some of the most relevant swarm robotics projects developed during the 2000s and 2010s, either as physical prototype platforms or as computational simulators and frameworks. Finally, an illustrative case study of a swarm robotics approach specialized to adhere to the principles and features of both the real-world behavior of social animals (microbats) and an associated swarm intelligence technique (bat algorithm) is discussed: bat robotics. The chapter describes a physical and logical realization of this approach along with some interesting applications. With these guidelines, the readers might find an inspiration to develop their own specialized swarm robotic approaches and apply them to interesting problems in several domains of knowledge. We project that this subject will become one of the most exciting lines of research in the field of swarm robotics for the next decades.