Eduardo Castello
Adaptive foraging for simulated and real robotic swarms: The dynamical response threshold approach
Castello, Eduardo; Yamamoto, Tomoyuki; Liu, Wenguo; Winfield, Alan F.T.; Nakamura, Yutaka; Ishiguro, Hiroshi
Authors
Tomoyuki Yamamoto
Wenguo Liu
Alan Winfield Alan.Winfield@uwe.ac.uk
Professor in Robotics
Yutaka Nakamura
Hiroshi Ishiguro
Abstract
Developing self-organised swarm systems capable of adapting to environmental changes as well as to dynamic situations is a complex challenge. An efficient labour division model, with the ability to regulate the distribution of work among swarm robots, is an important element of this kind of system. This paper extends the popular response threshold model and proposes a new adaptive response threshold model (ARTM). Experiments were carried out in simulation and in real-robot scenarios with the aim of studying the performance of this new adaptive model. Results presented in this paper verify that the extended approach improves on the adaptability of previous systems. For example, by reducing collision duration among robots in foraging missions, our approach helps small swarms of robots to adapt more efficiently to changing environments, thus increasing their self-sustainability (survival rate). Finally, we propose a minimal version of ARTM, which is derived from the conclusions drawn through real-robot and simulation results.
Citation
Castello, E., Yamamoto, T., Liu, W., Winfield, A. F., Nakamura, Y., & Ishiguro, H. (2016). Adaptive foraging for simulated and real robotic swarms: The dynamical response threshold approach. Swarm Intelligence, 10(1), 1-31
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 28, 2015 |
Publication Date | Jan 2, 2016 |
Deposit Date | Jan 7, 2016 |
Publicly Available Date | Jan 2, 2017 |
Journal | Swarm Intelligence |
Print ISSN | 1935-3812 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Issue | 1 |
Pages | 1-31 |
Keywords | adaptive foraging, cooperative behaviour, autonomous systems |
Public URL | https://uwe-repository.worktribe.com/output/915608 |
Publisher URL | http://link.springer.com/article/10.1007/s11721-015-0117-7 |
Additional Information | Additional Information : The final publication is available at Springer via http://dx.doi.org/10.1007/s11721-015-0117-7 |
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