This study considers a simple robot swarm navigation system based on shepherding in an environment with obstacles. Shepherding is a system in which a small number of control agents (shepherds and sheepdogs) indirectly guide several robots (sheep) by driving them from behind. Previous studies have predominantly focused on verifying proposed controllers based on numerical simulations and navigation experiments in well-prepared environments. However, additional shepherding experiments need to be conducted in environments with obstacles. This study aims to facilitate shepherding-type swarm robot navigation in an environment where a wall obstructs the goal. Usually, a high-end controller design is adopted for the robot to prevent it from getting trapped by obstacles. However, as the environment becomes more complex, the system design may become difficult. In contrast, this study proposes a simple shepherding navigation system based on creating and controlling “fields” to avoid obstacles. This research aims to verify whether the robot can be guided to a goal without obstacle recognition by creating an acoustic field based on the diffraction effects of sound. The proposed method modifies the previous shepherding models for sheep and shepherd robots to make them behave according to the acoustic field gradient. We demonstrate the validity of the proposed system by performing robot navigation for dog and sheep robots.

1. [1] T. J. Chong, X. J. Tang, C. H. Leng, M. Yogeswaran, O. E. Ng, and Y. Z. Chong, “Sensor technologies and simultaneous localization and mapping (slam),” Procedia Computer Science, Vol.76, pp. 174-179, 2015. https://doi.org/10.1016/j.procs.2015.12.336
2. [2] F. B. P. Malavazi, R. Guyonneau, J.-B. Fasquel, S. Lagrange, and F. Mercier, “Lidar-only based navigation algorithm for an autonomous agricultural robot,” Computers and Electronics in Agriculture, Vol.154, pp. 71-79, 2018. https://doi.org/10.1016/j.compag.2018.08.034
3. [3] H. Durrant-Whyte and T. Bailey, “Simultaneous localization and mapping: part i,” IEEE Robotics & Automation Magazine, Vol.13, No.2, pp. 99-110, 2006. https://doi.org/10.1109/MRA.2006.1638022
4. [4] N. Atanasov, J. L. Ny, K. Daniilidis, and G. J. Pappas, “Decentralized active information acquisition: Theory and application to multi-robot slam,” 2015 IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 4775-4782, 2015. https://doi.org/10.1109/ICRA.2015.7139863
5. [5] N. K. Long, K. Sammut, D. Sgarioto, M. Garratt, and H. A. Abbass, “A comprehensive review of shepherding as a bio-inspired swarm-robotics guidance approach,” IEEE Trans. on Emerging Topics in Computational Intelligence, Vol.4, No.4, pp. 523-537, 2020. https://doi.org/10.1109/TETCI.2020.2992778
6. [6] P. Nalepka, R. W. Kallen, A. Chemero, E. Saltzman, and M. J. Richardson, “Herd those sheep: Emergent multiagent coordination and behavioral-mode switching,” Psychological Science, Vol.28, No.5, pp. 630-650, 2017. https://doi.org/10.1177/0956797617692107
7. [7] A. A. Paranjape, S.-J. Chung, K. Kim, and D. H. Shim, “Robotic herding of a flock of birds using an unmanned aerial vehicle,” IEEE Trans. on Robotics, Vol.34, No.4, pp. 901-915, 2018. https://doi.org/10.1109/TRO.2018.2853610
8. [8] R. Vaughan, N. Sumpter, J. Henderson, A. Frost, and S. Cameron, “Experiments in automatic flock control,” Robotics and Autonomous Systems, Vol.31, No.1-2, pp. 109-117, 2000. https://doi.org/10.1016/S0921-8890(99)00084-6
9. [9] L. Gómez-Nava, R. Bon, and F. Peruani, “Intermittent collective motion in sheep results from alternating the role of leader and follower,” Nature Physics, Vol.18, pp. 1494-1501, 2022. https://doi.org/10.1038/s41567-022-01769-8
10. [10] W. Lee and D. Kim, “Autonomous shepherding behaviors of multiple target steering robots,” Sensors, Vol.17, No.12, Article No.2729, 2017. https://doi.org/10.3390/s17122729
11. [11] A. Pierson and M. Schwager, “Controlling noncooperative herds with robotic herders,” IEEE Trans. on Robotics, Vol.34, No.2, pp. 517-525, 2017. https://doi.org/10.1109/TRO.2017.2776308
12. [12] R. Himo, M. Ogura, and N. Wakamiya, “Iterative shepherding control for agents with heterogeneous responsivity,” Mathematical Biosciences and Engineering, Vol.19, No.4, pp. 3509-3525, 2022. https://doi.org/10.3934/mbe.2022162
13. [13] A. Fujioka, M. Ogura, and N. Wakamiya, “Shepherding algorithm for heterogeneous flock with model-based discrimination,” Advanced Robotics, Vol.37, No.1-2, pp. 99-114, 2022. https://doi.org/10.1080/01691864.2022.2133552
14. [14] Y. Sueoka, M. Ishitani, and K. Osuka, “Analysis of sheepdog-type robot navigation for goal-lost-situation,” Robotics, Vol.7, No.2, Article No.21, 2018. https://doi.org/10.3390/robotics7020021
15. [15] 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. https://doi.org/10.1109/SII46433.2020.9026218
16. [16] Y. Tsunoda, Y. Sueoka, T. Wada, and K. Osuka, “Design of mobile control for multiple agents inspired by sheepdog shepherding and its verification,” Trans. of the Institute of Systems, Control and Information Engineers, Vol.34, No.7, pp. 191-198, 2021 (in Japanese). https://doi.org/10.5687/iscie.34.191
17. [17] Y. Tsunoda, Y. Sueoka, and K. Osuka, “Experimental analysis of acoustic field control-based robot navigation,” J. Robot. Mechatron., Vol.31, No.1, pp. 110-117, 2019. https://doi.org/10.20965/jrm.2019.p0110
18. [18] T. Kida, Y. Sueoka, H. Shigeyoshi, Y. Tsunoda, Y. Sugimoto, and K. Osuka, “Verification of acoustic-wave-oriented simple state estimation and application to swarm navigation,” J. Robot. Mechatron., Vol.33, No.1, pp. 119-128, 2021. https://doi.org/10.20965/jrm.2021.p0119
19. [19] Y. Sueoka, D. D. Khanh, Y. Tsunoda, Y. Sugimoto, and K. Osuka, “Analysis and experiment of robot navigation by sound field using interaction with obstacles,” Trans. of the JSME, Vol.87, No.896, Article No.20-00280, 2021 (in Japanese). https://doi.org/10.1299/transjsme.20-00280
20. [20] 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. https://doi.org/10.1109/ROBIO.2017.8324588
21. [21] 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. https://doi.org/10.1080/01691864.2018.1539410
22. [22] Y. Tsunoda, Y. Sueoka, T. Wada, and K. Osuka, “Theoretical analysis of mobile control method for group agents motivated by sheepdog shepherding,” Trans. of the Society of Instrument and Control Engineers, Vol.55, No.8, pp. 507-515, 2019 (in Japanese). https://doi.org/10.9746/sicetr.55.507
23. [23] Y. Tsunoda, M. Ishitani, Y. Sueoka, and K. Osuka, “Analysis of sheepdog-type navigation for minimal sheep model,” The 3rd Int. Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM 2019), pp. 197-200, 2019.
24. [24] Y. Tsunoda, M. Ishitani, Y. Sueoka, and K. Osuka, “Analysis of sheepdog-type navigation for a sheep model with dynamics,” The Twenty-Fourth Int. Symposium on Artificial Life and Robotics 2019 (AROB 24th 2019), pp. 499-503, 2019.