A study of error diversity in robotic swarms for task partitioning in foraging tasks

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Often in swarm robotics, an assumption is made that all robots in the swarm behave the same and will have a similar (if not the same) error model. However, in reality this is not the case and this lack of uniformity in the error model, and other operations, can lead to various emergent behaviours. This paper considers the impact of the error model and compares robots in a swarm that operate using the same error model (uniform error) against each robot in the swarm having a different error model (thus introducing error diversity). Experiments are presented in the context of a foraging task. Simulation and physical experimental results show the importance of the error model and diversity in achieving expected swarm behaviour.
Original languageEnglish
Number of pages30
JournalFrontiers in Robotics and AI
Publication statusPublished - 4 Jan 2023

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  • swarm robotics
  • fault-tolerance
  • error diversity
  • Task partitioning
  • foraging

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