Spatial segregative behaviors in robotic swarms using differential potentials
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Spatial segregative behaviors in robotic swarms using differential potentials Vinicius G. Santos1 · Anderson G. Pires2 · Reza J. Alitappeh4 · Paulo A. F. Rezeck1 · Luciano C. A. Pimenta3 · Douglas G. Macharet1 · Luiz Chaimowicz1 Received: 14 June 2019 / Accepted: 9 June 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Segregative behaviors, in which individuals with common characteristics are placed together and set apart from other groups, are commonly found in nature. In swarm robotics, these behaviors can be important in different tasks that require a heterogeneous group of robots to be divided in homogeneous sets according to their physical (sensors, actuators) or logical (algorithms) capabilities. In this paper, we propose a controller that can spatially segregate a swarm of robots in two specific ways: clusters and concentric rings. By segregation, we mean that the swarm is partitioned in groups, with similar robots belonging to a same group, and these groups are spatially separated from each other. We achieve this by adapting and extending the differential potential concept, an abstraction of the mechanism by which cells achieve segregation. We present stability analysis and perform simulated experiments in 2D and 3D spaces in order to show the robustness of the proposed controller. Experiments with a limited number of real robots are also presented as a proof of concept. Results show that our approach allows a swarm of heterogeneous robots to segregate in a stable, compact, and collision-free fashion. Keywords Swarm robotics · Segregation · Artificial potential fields · Differential adhesion · Control
1 Introduction Robotic swarms are systems composed of a large number of robots that usually rely on selforganized behaviors in order to solve complex problems. Such systems have been receiving significant attention in recent years due to current advances in technology, which are allowing the mass production of increasingly smaller robots. Şahin (2005) defines swarm robotics as the study and implementation of methods that allow a large number of simple, physically embodied agents to achieve a desired collective behavior in a robust, flexible,
This work was supported by CAPES, CNPq, and Fapemig. * Luiz Chaimowicz [email protected] Extended author information available on the last page of the article
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and scalable manner. In a wide range of applications, these three properties provide key advantages such as low-cost distributed sensing, reduced chances of complete system failures, better workload distribution, and massive task parallelization. Research in swarm robotics usually focuses on homogeneous systems, in which all robots have the same physical characteristics (Dudek et al. 1996). However, several applications require the use of heterogeneous teams of agents in order to complete a given task, as sometimes it is not possible to integrate all of the required sensing and actuation capabilities in a single robot. One example
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