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Recent trends in robot learning and evolution for swarm robotics

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2023

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European Union (EU): 681872

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Frontiers in Robotics and AI. Frontiers. 2023, 10, 1134841. eISSN 2296-9144. Verfügbar unter: doi: 10.3389/frobt.2023.1134841

Zusammenfassung

Swarm robotics is a promising approach to control large groups of robots. However, designing the individual behavior of the robots so that a desired collective behavior emerges is still a major challenge. In recent years, many advances in the automatic design of control software for robot swarms have been made, thus making automatic design a promising tool to address this challenge. In this article, I highlight and discuss recent advances and trends in offline robot evolution, embodied evolution, and offline robot learning for swarm robotics. For each approach, I describe recent design methods of interest, and commonly encountered challenges. In addition to the review, I provide a perspective on recent trends and discuss how they might influence future research to help address the remaining challenges of designing robot swarms.

Zusammenfassung in einer weiteren Sprache

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004 Informatik

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swarm robotics, robot evolution, robot learning, automatic design, neuro-evolution, automatic modular design, embodied evolution, imitation learning

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ISO 690KUCKLING, Jonas, 2023. Recent trends in robot learning and evolution for swarm robotics. In: Frontiers in Robotics and AI. Frontiers. 2023, 10, 1134841. eISSN 2296-9144. Verfügbar unter: doi: 10.3389/frobt.2023.1134841
BibTex
@article{Kuckling2023-04-24Recen-71350,
  year={2023},
  doi={10.3389/frobt.2023.1134841},
  title={Recent trends in robot learning and evolution for swarm robotics},
  volume={10},
  journal={Frontiers in Robotics and AI},
  author={Kuckling, Jonas},
  note={Article Number: 1134841}
}
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