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Performance Evaluation of a Multi-Robot Search & Retrieval System: Experiences with MinDART

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Abstract

Swarm techniques, where many simple robots are used instead of complex ones for performing a task, promise to reduce the cost of developing robot teams for many application domains. The challenge lies in selecting an appropriate control strategy for the individual units. This work explores the effect of control strategies of varying complexity and environmental factors on the performance of a team of robots at a foraging task when using physical robots (the Minnesota Distributed Autonomous Robotic Team). Specifically we study the effect of localization and of simple indirect communication techniques on task completion time using two sets of foraging experiments. We also present results for task performance with varying team sizes and target distributions. As indicated by the results, control strategies with increasing complexity reduce the variance in the performance, but do not always reduce the time to complete the task.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Minnesota, 200 Union St. SE, Room 4-192, Minneapolis, MN, 55455-0159, USA

    Paul E. Rybski, Amy Larson, Harini Veeraraghavan, Monica Anderson & Maria Gini

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  1. Paul E. Rybski
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  2. Amy Larson
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  3. Harini Veeraraghavan
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  4. Monica Anderson
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  5. Maria Gini
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Correspondence to Maria Gini.

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Rybski, P.E., Larson, A., Veeraraghavan, H. et al. Performance Evaluation of a Multi-Robot Search & Retrieval System: Experiences with MinDART. J Intell Robot Syst 52, 363–387 (2008). https://doi.org/10.1007/s10846-008-9222-9

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  • DOI: https://doi.org/10.1007/s10846-008-9222-9

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