Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging

Date

2018-12-01

Author

Arvin, Farshad
Watson, Simon
Turgut, Ali Emre
Espinosa, Jose
Krajnik, Tomas
Lennox, Barry

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Swarm robotics studies the intelligent collective behaviour emerging from long-term interactions of large number of simple robots. However, maintaining a large number of robots operational for long time periods requires significant battery capacity, which is an issue for small robots. Therefore, re-charging systems such as automated battery-swapping stations have been implemented. These systems require that the robots interrupt, albeit shortly, their activity, which influences the swarm behaviour. In this paper, a low-cost on-the-fly wireless charging system, composed of several charging cells, is proposed for use in swarm robotic research studies. To determine the system's ability to support perpetual swarm operation, a probabilistic model that takes into account the swarm size, robot behaviour and charging area configuration, is outlined. Based on the model, a prototype system with 12 charging cells and a small mobile robot, Mona, was developed. A series of long-term experiments with different arenas and behavioural configurations indicated the model's accuracy and demonstrated the system's ability to support perpetual operation of multi-robotic system.

Subject Keywords

Swarm robotics, Wireless charging, Long-term autonomy, Perpetual swarm

URI

https://hdl.handle.net/11511/42019

Journal

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS

DOI

https://doi.org/10.1007/s10846-017-0673-8

Collections

Department of Mechanical Engineering, Article

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Citation Formats

F. Arvin, S. Watson, A. E. Turgut, J. Espinosa, T. Krajnik, and B. Lennox, “Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging,” JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, pp. 395–412, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42019.