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Recruitment-Based Robotic Colony Allocation

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Distributed Autonomous Robotic Systems

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 9))

Abstract

Robotic colonies for distributed field operations require intelligent algorithms for allocating assets based on time-varying task requirements. Agricultural applications, including crop pollination, involve dynamic schedules that are unknown a priori; thus, an effective colony must characterize task completion and respond to perceived changes. Insect colonies rely on individuals’ observations to allocate their workforces to tasks, such as foraging in the richest flower patches. Biologically-inspired strategies for gathering observations while providing field coverage were formulated and integrated into a colony recruitment model. The strategies’ coverage results and efficiency were evaluated with varying task schedules, colony placements, and multiple colonies, yielding 50–100% pollination across all independent variables. Splitting a single colony into multiple small colonies improved coverage and efficiency.

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Acknowledgements

This research was supported by a Graduate Teaching Assistantship from the College of Engineering at Oregon State University.

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Authors and Affiliations

  1. Collaborative Robotics & Intelligent Systems Institute, Oregon State University, Corvallis, OR, 97331, USA

    Chloe Fleming & Julie A. Adams

Authors
  1. Chloe Fleming
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  2. Julie A. Adams
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Corresponding author

Correspondence to Chloe Fleming .

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Editors and Affiliations

  1. Department of Computer Science, University of Colorado Boulder, Boulder, CO, USA

    Nikolaus Correll

  2. Department of Aeronautics and Astronautics, Stanford University, Stanford, CA, USA

    Mac Schwager

  3. Department of Aerospace Engineering, University of Maryland, College Park, MD, USA

    Michael Otte

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Fleming, C., Adams, J.A. (2019). Recruitment-Based Robotic Colony Allocation. In: Correll, N., Schwager, M., Otte, M. (eds) Distributed Autonomous Robotic Systems. Springer Proceedings in Advanced Robotics, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-030-05816-6_6

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