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No robot left behind: coordination to overcome local minima in swarm navigation

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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No robot left behind: coordination to overcome local minima in swarm navigation. / Soriano Marcolino, Leandro; Chaimowicz, Luiz.
Proceedings of the 2008 IEEE International Conference on Robotics and Automation. Pasadena, California, 2008. p. 1904-1909 (Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Soriano Marcolino, L & Chaimowicz, L 2008, No robot left behind: coordination to overcome local minima in swarm navigation. in Proceedings of the 2008 IEEE International Conference on Robotics and Automation. Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on, Pasadena, California, pp. 1904-1909. https://doi.org/10.1109/ROBOT.2008.4543485

APA

Soriano Marcolino, L., & Chaimowicz, L. (2008). No robot left behind: coordination to overcome local minima in swarm navigation. In Proceedings of the 2008 IEEE International Conference on Robotics and Automation (pp. 1904-1909). (Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on).. https://doi.org/10.1109/ROBOT.2008.4543485

Vancouver

Soriano Marcolino L, Chaimowicz L. No robot left behind: coordination to overcome local minima in swarm navigation. In Proceedings of the 2008 IEEE International Conference on Robotics and Automation. Pasadena, California. 2008. p. 1904-1909. (Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on). doi: 10.1109/ROBOT.2008.4543485

Author

Soriano Marcolino, Leandro ; Chaimowicz, Luiz. / No robot left behind : coordination to overcome local minima in swarm navigation. Proceedings of the 2008 IEEE International Conference on Robotics and Automation. Pasadena, California, 2008. pp. 1904-1909 (Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on).

Bibtex

@inproceedings{df5951184e22484f90c04bdc9677f1e3,
title = "No robot left behind: coordination to overcome local minima in swarm navigation",
abstract = "In this paper, we address navigation and coordination methods that allow swarms of robots to converge and spread along complex 2D shapes in environments containing unknown obstacles. Shapes are modeled using implicit functions and a gradient descent approach is used for controlling the swarm. To overcome local minima, that may appear in these scenarios, we use a coordination mechanism that reallocates some robots as “rescuers” and sends them to help other robots that may be trapped. Simulations and real experiments demonstrate the feasibility of the proposed approach.",
author = "{Soriano Marcolino}, Leandro and Luiz Chaimowicz",
year = "2008",
doi = "10.1109/ROBOT.2008.4543485",
language = "English",
isbn = "9781424416462",
series = "Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on",
publisher = "IEEE",
pages = "1904--1909",
booktitle = "Proceedings of the 2008 IEEE International Conference on Robotics and Automation",

}

RIS

TY - GEN

T1 - No robot left behind

T2 - coordination to overcome local minima in swarm navigation

AU - Soriano Marcolino, Leandro

AU - Chaimowicz, Luiz

PY - 2008

Y1 - 2008

N2 - In this paper, we address navigation and coordination methods that allow swarms of robots to converge and spread along complex 2D shapes in environments containing unknown obstacles. Shapes are modeled using implicit functions and a gradient descent approach is used for controlling the swarm. To overcome local minima, that may appear in these scenarios, we use a coordination mechanism that reallocates some robots as “rescuers” and sends them to help other robots that may be trapped. Simulations and real experiments demonstrate the feasibility of the proposed approach.

AB - In this paper, we address navigation and coordination methods that allow swarms of robots to converge and spread along complex 2D shapes in environments containing unknown obstacles. Shapes are modeled using implicit functions and a gradient descent approach is used for controlling the swarm. To overcome local minima, that may appear in these scenarios, we use a coordination mechanism that reallocates some robots as “rescuers” and sends them to help other robots that may be trapped. Simulations and real experiments demonstrate the feasibility of the proposed approach.

U2 - 10.1109/ROBOT.2008.4543485

DO - 10.1109/ROBOT.2008.4543485

M3 - Conference contribution/Paper

SN - 9781424416462

T3 - Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on

SP - 1904

EP - 1909

BT - Proceedings of the 2008 IEEE International Conference on Robotics and Automation

CY - Pasadena, California

ER -