Titlebook: Swarm Robotics: A Formal Approach; Heiko Hamann Book 2018 Springer International Publishing AG 2018 Computational complexity.Self-assembly

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Short Introduction to Robotics,ting from a general perspective and quickly introduces fundamental concepts, such as sensors, actuators, and kinematics. We continue with a short introduction to open-loop and closed-loop control. Agent models, behavior-based robotics, and potential field control are introduced as control options pa

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Scenarios of Swarm Robotics,guide through the literature on swarm robotics. It is structured by the investigated scenarios and starts from tasks of low complexity, such as aggregation and dispersion. A discussion of pattern formation, object clustering, sorting, and self-assembly follows. Collective construction is already a r

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Modeling Swarm Systems and Formal Design Methods,as a dimension reduction technique for swarm robotics. Then we start from a discussion of local sampling, which is the challenge in swarm robotics of dealing with local information. The local samples are not representative for the whole swarm and hence we require a methodology to work with unreliabl

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Collective Decision-Making,ill for a swarm of robots in order to form an autonomous system also on the macroscopic level. We start with traditional methods to describe decision-making and rational agents. Group decision-making is introduced and we investigate the example of collective motion as a decision-making process. It f

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Case Study: Adaptive Aggregation,es that one requires to design a system of swarm robots. The task is rather simple and we focus on adaptive aggregation, that is, the swarm has to aggregate at a particular spot determined by environmental features. We follow a biological role model and apply standard modeling techniques of swarm ro

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Book 2018methods that allow readers to understand how to design large-scale robot systems by going through many example scenarios on topics such as aggregation, coordinated motion (flocking), task allocation, self-assembly, collective construction, and environmental monitoring. The author explains the method

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Collective Decision-Making, model, Kuramoto model, Ising model, fiber bundle model, and sociophysics by Serge Galam among other approaches. We conclude with a discussion of hardware implementations of collective decision-making in swarm robotics.

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