Publicado:

2021-12-24

Número:

Vol. 18 Núm. 2 (2021): Revista Tekhnê

Sección:

Artículos

Swarm behavior simulator with bacterial Quorum Sensing

Simulador de comportamiento de enjambre con Quorum Sensing bacteriano

Autores/as

  • Eyder A. Rodríguez C. Universidad Distrital Francisco José de Caldas
  • Daniel M. Romero S. Universidad Distrital Francisco José de Caldas

Palabras clave:

Path-planning, quorum sensing, simulator, software, swarm (en).

Palabras clave:

Enjambre, Planificación de rutas, quorum sensing, simulador, software (es).

Resumen (en)

One of the most useful tools in the design of path-planning solutions is simulators. Thanks to them, it is possible to predict the performance of certain control strategies. In this paper, a simulator is presented that implements a swarm of automatons, which perform a wild motion in a user-selected environment. The robots will have the quality to avoid collisions with different obstacles that affect their mobility since they are equipped with proximity sensors. The interface of this simulator was designed entirely with the Qt Designer software. Successful configurations that replicate the performance of the real prototype are presented.

 

Resumen (es)

Una de las herramientas más útiles en el diseño de soluciones de planificación de trayectorias son los simuladores. Gracias a ellos, es posible predecir el rendimiento de determinadas estrategias de control. En este trabajo se presenta un simulador que implementa un enjambre de autómatas que realizan un movimiento salvaje en un entorno seleccionado por el usuario. Los robots tendrán la cualidad de evitar colisiones con diferentes obstáculos que afecten a su movilidad ya que están equipados con sensores de proximidad. La interfaz de este simulador se ha diseñado íntegramente con el software Qt Designer. Se presentan configuraciones exitosas que replican el desempeño del prototipo real.

 

Biografía del autor/a

Eyder A. Rodríguez C., Universidad Distrital Francisco José de Caldas

 

 

Daniel M. Romero S., Universidad Distrital Francisco José de Caldas

 

 

Referencias

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Flikkema, P., & Leid, J. (2005). Bacterial communities: A microbiological model for swarm intelligence. Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005. https://doi.org/10.1109/sis.2005.1501655

Gómez, P., & Rodríguez, A. (2011). Simulating a rock-scissors-paper bacterial game with a discrete cellular automaton. In New challenges on bioinspired applications (pp. 363–370). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-21326-7_39

Hsieh, M. A., Halász, Á., Berman, S., & Kumar, V. (2008). Biologically inspired redistribution of a swarm of robots among multiple sites. Swarm Intelligence, 2(2-4), 121–141. https://doi.org/10.1007/s11721-008-0019-z

Huang, C. X., Zhang, B., Deng, A.-C., & Swirski, B. (1995). The design and implementation of PowerMill. Proceedings of the 1995 international symposium on Low power design - ISLPED ’95. https://doi.org/10.1145/224081.224100

Ichter, B., Harrison, J., & Pavone, M. (2018). Learning sampling distributions for robot motion planning. 2018 IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/icra.2018.8460730

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Martínez, F., Jacinto, E., & Hernández, C. (2012). Particle diffusion model applied to the swarm robots navigation. Tecnura, 16(2012), 34–43.

Martínez, F., Martínez, F., & Montiel, H. (2020). Bacterial quorum sensing applied to the coordination of autonomous robot swarms. Bulletin of Electrical Engineering and Informatics, 9(1), 67–74. https://doi.org/10.11591/eei.v9i1.1538

Mohanan, M., & Salgoankar, A. (2018). A survey of robotic motion planning in dynamic environments. Robotics and Autonomous Systems, 100(2018), 171–185. https://doi.org/10.1016/j.robot.2017.

011

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Cómo citar

APA

Rodríguez C., E. A., y Romero S., D. M. (2021). Swarm behavior simulator with bacterial Quorum Sensing. Tekhnê, 18(2), 25–36. https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20324

ACM

[1]
Rodríguez C., E.A. y Romero S., D.M. 2021. Swarm behavior simulator with bacterial Quorum Sensing. Tekhnê. 18, 2 (dic. 2021), 25–36.

ACS

(1)
Rodríguez C., E. A.; Romero S., D. M. Swarm behavior simulator with bacterial Quorum Sensing. Tekhnê 2021, 18, 25-36.

ABNT

RODRÍGUEZ C., Eyder A.; ROMERO S., Daniel M. Swarm behavior simulator with bacterial Quorum Sensing. Tekhnê, [S. l.], v. 18, n. 2, p. 25–36, 2021. Disponível em: https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20324. Acesso em: 17 jul. 2024.

Chicago

Rodríguez C., Eyder A., y Daniel M. Romero S. 2021. «Swarm behavior simulator with bacterial Quorum Sensing». Tekhnê 18 (2):25-36. https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20324.

Harvard

Rodríguez C., E. A. y Romero S., D. M. (2021) «Swarm behavior simulator with bacterial Quorum Sensing», Tekhnê, 18(2), pp. 25–36. Disponible en: https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20324 (Accedido: 17 julio 2024).

IEEE

[1]
E. A. Rodríguez C. y D. M. Romero S., «Swarm behavior simulator with bacterial Quorum Sensing», Tekhnê, vol. 18, n.º 2, pp. 25–36, dic. 2021.

MLA

Rodríguez C., Eyder A., y Daniel M. Romero S. «Swarm behavior simulator with bacterial Quorum Sensing». Tekhnê, vol. 18, n.º 2, diciembre de 2021, pp. 25-36, https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20324.

Turabian

Rodríguez C., Eyder A., y Daniel M. Romero S. «Swarm behavior simulator with bacterial Quorum Sensing». Tekhnê 18, no. 2 (diciembre 24, 2021): 25–36. Accedido julio 17, 2024. https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20324.

Vancouver

1.
Rodríguez C. EA, Romero S. DM. Swarm behavior simulator with bacterial Quorum Sensing. Tekhnê [Internet]. 24 de diciembre de 2021 [citado 17 de julio de 2024];18(2):25-36. Disponible en: https://revistas.udistrital.edu.co/index.php/tekhne/article/view/20324

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