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A Sequential Task Addition Distributed Assignment Algorithm for Multi-Robot Systems

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Abstract

In this paper, we present a novel distributed task-allocation algorithm, namely the Sequential Task Addition Distributed Assignment Algorithm (STADAA), for autonomous multi-robot systems. The proposed STADAA can implemented in applications such as search and rescue, mobile-target tracking, and Intelligence, Surveillance, and Reconnaissance (ISR) missions. The proposed STADAA is developed by modifying an algorithm (i.e., the Task Oriented Distributed Assignment Algorithm (TODAA)) we previously developed based on the Hungarian algorithm. The STADAA employs a conflict-resolution mechanism that utilizes a slack variable, sequentially adding new admissible tasks to an admissible task list when there exists conflict in an assignment. The STADAA aims to minimize the resulting cost of the task assignments. We compare the STADAA with the Consensus-Based Auction Algorithm (CBAA), the Distributed Hungarian Based Algorithm (DHBA), and the TODAA in terms of the computational time, optimality, the number of steps to converge, and algorithmic complexity. The results show that the STADAA outperforms the CBAA and the TODAA in optimality and outperforms the DHBA in computational time.

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Data Availability

The supporting data of the information presented in this manuscript is available from the corresponding author, Nathan Lindsay, upon reasonable request.

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Funding

This work was supported by the New Mexico Space Grant Consortium and the Laboratory Directed Research and Development program at Sandia National Laboratories. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology Engineering Solutions of Sandia, LLC, a wholly-owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. The views expressed in the article do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

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Authors and Affiliations

  1. New Mexico State University, Las Cruces, NM, USA

    Nathan Lindsay, Russell K. Buehling & Liang Sun

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  1. Nathan Lindsay
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  2. Russell K. Buehling
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  3. Liang Sun
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Contributions

The first author, Nathan Lindsay, developed the algorithm proposed (Sequential Task Addition Distributed Assignment Algorithm - STADAA) in this paper and developed the code for the STADAA, the Consensus Based Auction Algorithm, and the Task Oriented Distributed Assignment Algorithm, which were all used in testing. Also, he wrote the first draft of this manuscript, analyzing the test results and providing insight into the algorithm’s performance. The second author, Russell Buehling, developed the code for the Distributed Hungarian Based Algorithm that was used in testing, developed the testing environment and ran the tests that generated the results displayed in this paper. The third author, Liang Sun, as the research advisor of the first and second authors, initiated the research work presented in the paper, developed the research plan for methodologies, simulations, experiments, analysis, and data collection, provided guidance for research discussions. All authors read and approved the revised manuscript.

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Correspondence to Nathan Lindsay.

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Previous paper “A Task-Oriented Distributed Assignment Algorithm for Collaborative Unmanned Aerial Systems” in proceedings of the 2020 International Conference on Unmanned Aircraft Systems (ICUAS’20), Athens, Greece

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Lindsay, N., Buehling, R.K. & Sun, L. A Sequential Task Addition Distributed Assignment Algorithm for Multi-Robot Systems. J Intell Robot Syst 102, 51 (2021). https://doi.org/10.1007/s10846-021-01394-2

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