Abstract
Two prominent categories of algorithms for achieving coordinated multi-robot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. Although typically they are treated separately, we believe that a combination of flock and formation control represents a promising algorithmic solution. Such an algorithm could take advantage of a combination of characteristics of both categories that are best suited for a given situation. Therefore, in this work, we propose two distributed algorithms capable of gradually and reversibly shifting between flocking and formation behaviors using a single parameter \(\mathcal {W}\). We evaluate them using both simulated and real robots with and without the presence of obstacles. We find that both algorithms successfully trade off flock density for formation error. Furthermore, leveraging a narrow passage experiment as an application case study, we demonstrate that an adaptive shift between flock and formation behavior, adopting a simple method to define \(\mathcal {W}\) in real-time using exclusively on-board resources, results in a statistically relevant reduction of traversing time in comparison to a non-adaptive formation control algorithm.
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Acknowledgements
We would like to thank Masaki Haruna, Masahiko Kurishige and Tomoki Emmei of the Advanced Technology R &D Center, Mitsubishi Electric Corporation, Amagasaki City, Japan for the fruitful technical discussions all along this work. This work is financially supported by Mitsubishi Electric Corporation, Japan.
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A video of the experiments performed for this contribution can be found on our research web page: www.epfl.ch/labs/disal/research/mrsmodelingcontrol.
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Baumann, C., Perolini, J., Tourki, E., Martinoli, A. (2024). Hybrid Flock - Formation Control Algorithms. In: Bourgeois, J., et al. Distributed Autonomous Robotic Systems. DARS 2022. Springer Proceedings in Advanced Robotics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-031-51497-5_37
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