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Avoiding target congestion on the navigation of robotic swarms

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Abstract

Robotic swarms are decentralized systems formed by a large number of robots. A common problem encountered in a swarm is congestion, as a great number of robots often must move towards the same region. This happens when robots have a common target, for example during foraging or waypoint navigation. We propose three algorithms to alleviate congestion: in the first, some robots stop moving towards the target for a random number of iterations; in the second, we divide the scenario in two regions: one for the robots that are moving towards the target, and another for the robots that are leaving the target; in the third, we combine the two previous algorithms. We evaluate our algorithms in simulation, where we show that all of them effectively improve navigation. Moreover, we perform an experimental analysis in the real world with ten robots, and show that all our approaches improve navigation with statistical significance.

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Acknowledgments

This work was partially supported by CAPES, CNPq, and FAPEMIG.

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Authors and Affiliations

  1. Teamcore Laboratory, Computer Science Department, University of Southern California, Los Angeles, CA, USA

    Leandro Soriano Marcolino

  2. Centro de Ciências Exatas e Tecnológicas, Universidade Federal do Recôncavo da Bahia, Cruz das Almas, BA, Brazil

    Yuri Tavares dos Passos & Andersoney dos Santos Rodrigues

  3. VeRLab - Vision and Robotics Laboratory, Computer Science Department, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    Álvaro Antônio Fonseca de Souza & Luiz Chaimowicz

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  1. Leandro Soriano Marcolino
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  2. Yuri Tavares dos Passos
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  3. Álvaro Antônio Fonseca de Souza
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  4. Andersoney dos Santos Rodrigues
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  5. Luiz Chaimowicz
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Correspondence to Leandro Soriano Marcolino.

Appendix: PCC-EE with ORCA

Appendix: PCC-EE with ORCA

In Fig. 27 we show screenshots of the PCC-EE algorithm using ORCA to avoid collisions (instead of using local repulsion forces). Figure 27a shows the initial position of the robots. Robots in the exit region move towards the entry region, while the robots in the entry region follow the PCC algorithm (Fig. 27b). We notice in Fig. 27c that some robots are able to reach the target, but others form an arc in the entry region. All robots that were not in the arc are able to reach the target. However, the robots in the arc stay in equilibrium, and are not able to leave anymore (Fig. 27d, e, f).

This situation is similar to the one discussed in the main paper: as all velocity vectors point towards the target, the resulting velocity vector of all robots in the arc points towards the perpendicular of the preferred velocity vector (towards the target). This time, however, the robots in the borderline of the entry region are not able to leave the area, as they immediately return to the entry region due to the PCC-EE algorithm. Hence, instead of circulating around the target area, the robots stay locked in arcs around the target area.

Fig. 27
figure 27

Execution screenshots of the PCC-EE algorithm, using ORCA to avoid collisions (video available at https://youtu.be/ch0v2jje56E). a 0 s Beginning of the execution. b 4 min 30 s Robots move towards the entry region, following the PCC algorithm inside it. c 9 min 0 s Some robots are able to reach the target, but others form an arc in the entry region, surrounding the target. d 13 min 30 s The robots that were not in the arcs around the target are able to reach the target. e 18 min 0 s The robots in the arcs still do not converge towards the target. f 22 min 31 s After many iterations, the robots still do not go towards the target, locked in the arcs in the entry region

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Soriano Marcolino, L., Tavares dos Passos, Y., Fonseca de Souza, Á. et al. Avoiding target congestion on the navigation of robotic swarms. Auton Robot 41, 1297–1320 (2017). https://doi.org/10.1007/s10514-016-9577-x

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