JRM Vol.35 No.4 pp. 948-956
doi: 10.20965/jrm.2023.p0948


Exploration of a Simple Navigation Method for Swarm Robots Pioneered by Heterogeneity

Yuichiro Sueoka ORCID Icon, Mitsuki Okada, Yusuke Tsunoda ORCID Icon, Yasuhiro Sugimoto ORCID Icon, and Koichi Osuka ORCID Icon

Department of Mechanical Engineering, Osaka University
2-1 Yamadaoka, Suita, Osaka 565-0871, Japan

February 20, 2023
May 18, 2023
August 20, 2023
group navigation with heterogeneity, swarm robots, simple navigation

In recent years, research has been conducted on swarm robot systems in which multiple autonomous mobile robots cooperate to perform tasks. Swarm robot systems are expected to perform high functionality as a group by cooperating with each other, in spite of the limited capabilities of the individual robots. This paper explores a method of simplifying swarm robot controllers as much as possible for swarm robot navigation. If we can achieve autonomous navigation of swarm robots to a target area with minimal resource consumption, they only need to implement the task execution function in that area. This leads to lower costs for swarm robot design and more efficient system architecture design. To address the above aims, this study focuses on heterogeneity. Specifically, we introduce a navigator robot that indirectly guides swarm robots named the worker robots. Heterogeneity in this paper refers to the worker robots and the navigator robots. We design the interaction between the navigator robot and the worker robots to provide a system that guides the worker robots to the destination.

Heterogeneity-based swarm robot navigation

Heterogeneity-based swarm robot navigation

Cite this article as:
Y. Sueoka, M. Okada, Y. Tsunoda, Y. Sugimoto, and K. Osuka, “Exploration of a Simple Navigation Method for Swarm Robots Pioneered by Heterogeneity,” J. Robot. Mechatron., Vol.35 No.4, pp. 948-956, 2023.
Data files:
  1. [1] M. Brambilla, E. Ferrante, M. Birattari, and M. Dorigo, “Swarm robotics: A review from the swarm engineering perspective,” Swarm Intelligence, Vol.7, No.1, pp. 1-41, 2013.
  2. [2] T. Arai, E. Pagello, and L. E. Parker, “Editorial: Advances in multi-robot systems,” IEEE Trans. Robot. Autom., Vol.18, No.5, pp. 655-661, 2002.
  3. [3] L. Bayindir, “A review of swarm robotics tasks,” Neurocomputing, Vol.172, pp. 292-321, 2016.
  4. [4] E. Sahin, “Swarm Robotics: From Sources of Inspiration to Domains of Application,” Swarm Robotics, Vol.3342, pp. 10-20, 2005.
  5. [5] E. Tuci, M. H. M. Alkilabi, and O. Akanyeti, “Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art,” Frontiers in Robotics and AI, Vol.5, Article No.59, 2018.
  6. [6] Z. Wang and M. Schwager, “Kinematic Multi-Robot Manipulation with no Communication Using Force Feedback,” 2016 IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 427-432, 2016.
  7. [7] J. Werfel, K. Petersen, and R. Nagpal, “Designing Collective Behavior in a Termite-Inspired Robot Construction Team,” Science, Vol.343, No.6172, pp. 754-758, 2014.
  8. [8] K. Sakurama, S. Azuma, and T. Sugie, “Multiagent Coordination Via Distributed Pattern Matching,” IEEE Trans. on Automatic Control, Vol.64, No.8, pp. 3210-3225, 2019.
  9. [9] K. Sakurama, “Unified Formulation of Multiagent Coordination With Relative Measurements,” IEEE Trans. on Automatic Control, Vol.66, No.9, pp. 4101-4116, 2021.
  10. [10] M. Rubenstein, A. Cornejo, and R. Nagpal, “Programmable self-assembly in a thousand-robot swarm,” Science, Vol.345, No.6198, pp. 795-799, 2014.
  11. [11] K. Nagatani et al., “Innovative technologies for infrastructure construction and maintenance through collaborative robots based on an open design approach,” Advanced Robotics, Vol.35, No.11, pp. 715-722, 2021.
  12. [12] D. Sakai, H. Fukushima, and F. Matsuno, “Leader-Follower Navigation in Obstacle Environments While Preserving Connectivity Without Data Transmission,” IEEE Trans. on Control Systems Technology, Vol.26, No.4, pp. 1233-1248, 2018.
  13. [13] D. Panagou and V. Kumar, “Cooperative visibility maintenance for leader-follower formations in obstacle environments,” IEEE Trans. Robot., Vol.30, No.4, pp. 831-844, 2014.
  14. [14] A. Cezayirli and F. Kerestecioglu, “Navigation of non-communicating autonomous mobile robots with guaranteed connectivity,” Robotica, Vol.31, No.5, pp. 767-776, 2013.
  15. [15] R. Vaughan, N. Sumpter, A. Frost, and S. Cameron, “Robot sheepdog project achieves automatic flock control,” Proc. of Int. Conf. on Simulation of Adaptive Behaviour, 1998.
  16. [16] D. Strömbom, R. P. Mann, A. M. Wilson, S. Hailes, A. J. Morton, D. J. Sumpter, and A. J. King, “Solving the shepherding problem: Heuristics for herding autonomous interacting agents,” J. of the Royal Society Interface, Vol.11, No.100, Article No.20140719, 2014.
  17. [17] W. Lee and D. Kim, “Autonomous shepherding behaviors of multiple target steering robots,” Sensors, Vol.17, No.12, Article No.2729, 2017.
  18. [18] Y. Tsunoda, Y. Sueoka, and K. Osuka, “On statistical analysis for shepherd guidance system,” 2017 IEEE Int. Conf. on Robotics and Biomimetics (ROBIO), pp. 1246-1251, 2017.
  19. [19] Y. Sueoka, T. Kita, M. Ishikawa, and K. Osuka, “Analysis of Sheepdog-Type Robot Navigation for Goal-Lost-Situation,” Robotics, Vol.7, No.2, Article No.21, 2018.
  20. [20] Y. Tsunoda, Y. Sueoka, Y. Sato, and K. Osuka, “Analysis of local-camera-based shepherding navigation,” Advanced Robotics, Vol.32, No.23, pp. 1217-1228, 2018.
  21. [21] Y. Tsunoda, Y. Sueoka, T. Wada, and K. Osuka, “Sheepdog-type robot navigation: Experimental verification based on a linear model,” 2020 IEEE/SICE Int. Symposium on System Integration (SII), pp. 1144-1149, 2020.
  22. [22] M. Dorigo et al., “Swarmanoid: A novel concept for the study of heterogeneous robotic swarm,” IEEE Robot Autom. Mag., Vol.20, No.4, pp. 60-71, 2013.
  23. [23] R. Maeda, T. Endo, and F. Matsuno, “Decentralized Navigation for Heterogeneous Swarm Robots With Limited Field of View,” IEEE Robotics and Automation Letters, Vol.2, No.2, pp. 904-911, 2017.
  24. [24] L. Sabattini, C. Secchi, and N. Chopra, “Decentralized Estimation and Control for Preserving the Strong Connectivity of Directed Graphs,” IEEE Trans. Cybern., Vol.45, No.10, pp. 2273-2286, 2015.

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