Investigating feasible tool for swarm robotic based oil skimming application

  • Authors

    • Padma Priya R
    • Agarwal Ruchi Sanjay
    • Yesho Vardhan Gupta
    • D Rekha
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.15542
  • Distributed System, Oil Skimming, Swarm Robots, Simulation Software.

  • Abstract

    Swarm Robots, a multi-robot system (inspired from insect- groups), work in a decentralized network in a distributed manner [1]. These group of robots coordinate their activities without the need of a universal leader. Instead, they use local rules to track the behavior of the whole group and to communicate information amongst each other. Proper implementation of the swarm robotics system includes executing tasks such as aggregation, assembling, path planning, and pattern formation [2]. Various algorithms may be implemented to realize these tasks and techniques the robots carry out. These algorithms need to be exhaustively tested in terms of robustness, safety and efficiency. Testing of these systems in real-time environments is a matter of great risk to both the resources as well as life. Hence, simulators play a crucial role in the research of swarm robots, more so in applications which require close interaction with the humans [3]. It is equally important to have efficient simulators as it is to have algorithms pertaining to swarm robotics. This study presents a meticulous overview of popular robotic simulation software, some of which could also be used for interfacing in the real robotic environment. A comparison with reference to the oil skimming from oceans using swarm robots as mentioned in the paper is made between the most feasible simulation environments. This is followed by an illustration of the various tasks to be performed by individual robots or group of them.

  • References

    1. I. Navarro and F. Matía, “An Introduction to Swarm Robotics,” ISRN Robot. vol. 2013, pp. 1–10, 2013.
    2. L. Bayindir, “A review of swarm robotics tasks,” Neurocomputing, vol. 172, pp. 292–321, 2016.
    3. A. Staranowicz and G. L. Mariottini, “A survey and comparison of commercial and open-source robotic simulator software,” Proc. 4th Int. Conf. PErvasive Technol. Relat. To Assist. Environ. - PET-RA ’11, p. 1, 2011.
    4. M. Duarte et al., “Application of Swarm Robotic Systems to Marine Environmental Monitoring,” Proc. IEEE/MTS Ocean. pp. 1–8, 2016.
    5. R. Mendonça, P. Santana, F. Marques, A. Lourenço, J. Silva, and J. Barata, “Kelpie: A ROS-based multi-robot simulator for water sur-face and aerial vehicles,” Proc. - 2013 IEEE Int. Conf. Syst. Man, Cybern. SMC 2013, no. January 2014, pp. 3645–3650, 2013.
    6. T. Tosik, J. Schwinghammer, M. J. Feldvoß, J. P. Jonte, A. Brech, and E. Maehle, “MARS: A simulation environment for marine swarm robotics and environmental monitoring,” Ocean. 2016 - Shanghai, 2016.
    7. C. Dixon, A. F. T. Winfield, M. Fisher, and C. Zeng, “Towards temporal verification of swarm robotic systems,” Rob. Auton. Syst., vol. 60, no. 11, pp. 1429–1441, 2012.
    8. R. C. Harrel, “Effects of a crude oil spill on water quality and mac-robenthos of a southeast Texas stream,” Hydrobiologia, vol. 124, no. 3, pp. 223–228, 1985.
    9. A. Jevtic and D. Andina, “Swarm Intelligence and Its Applications in Swarm Robotics,” Proc. 6th Wseas Int. Conf. Comput. Intell. ManMachine Syst. Cybern., no. January, pp. 41–46, 2007.
    10. N. M. P. Kakalis and Y. Ventikos, “Robotic swarm concept for ef-ficient oil spill confrontation,” J. Hazard. Mater. vol. 154, no. 1–3, pp. 880–887, 2008.
    11. L. Silva and N. Nedjah, “Efficient strategy for collective navigation control in swarm robotics,” Procedia Comput. Sci., vol. 80, pp. 814–823, 2016.
    12. P. Walker, S. Amirpour Amraii, N. Chakraborty, M. Lewis, and K. Sycara, “Human control of robot swarms with dynamic leaders,” IEEE Int. Conf. Intell. Robot. Syst., pp. 1108–1113, 2014.
    13. Dhurandher, S. K., Misra, S., Obaidat, M. S., & Khairwal, S. UWSim: A simulator for underwater sensor networks. Simulation, 84(7), 327-338, 2008
    14. The Hindu. (2018). Chennai oil spill. [online] Available at: http://www.thehindu.com/news/cities/chennai/chennai-oil-spill/article17170741.ece1 [Accessed 15 Mar. 2018].
    15. The Hindu. (2018). A slick on the shore and the murky aftermath. [online] Available at: http://www.thehindu.com/news/cities/chennai/a-slick-on-the-shore-and-the-murky-aftermath/article17290268.ece1 [Accessed 15 Mar. 2018].
    16. Anon, (2018). [online] Available at: http://www.thehindu.com/news/cities/chennai/As-clean-up-continues-oil-spill-reaches-Mamallapuram/article17295236.ece [Ac-cessed 15 Mar. 2018].
    17. Anon, (2018). [online] Available at: http://spectrum.ieee.org/automaton/robotics/robotics-software/microsoft-shuts-down-its-robotics-grouphtt [Accessed 15 Mar. 2018].
    18. IIT Madras' Bluetooth-controlled robots sweep area clean, e. (2018).45 Bluetooth-controlled robots by IIT Madras students swept an area clean, enter records. [online] YourStory.com. Availa-ble at: https://yourstory.com/2017/11/iit-madras-robots/ [Accessed 15 Mar. 2018.

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  • How to Cite

    Priya R, P., Ruchi Sanjay, A., Vardhan Gupta, Y., & Rekha, D. (2018). Investigating feasible tool for swarm robotic based oil skimming application. International Journal of Engineering & Technology, 7(2.33), 960-967. https://doi.org/10.14419/ijet.v7i2.33.15542

    Received date: 2018-07-13

    Accepted date: 2018-07-13

    Published date: 2018-06-08