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A two-stage framework for fair autonomous robot deployment using virtual forces

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  • Sallam, Gamal
  • Baroudi, Uthman

Abstract

Consider a set of landmarks that are distributed in an emergency scene and each needs a specific number of robots in its vicinity. This paper presents a two-stage framework for deploying robots autonomously for such scenarios. In the first stage, a Two-hop Cooperative Virtual Force Robot Deployment (Two-hop COVER) technique is employed. It expedites the deployment process by establishing a cooperative relationship between robots and neighboring landmarks. Two-hop communication is utilized as well to reduce the deployment time and traveled distance by robots to satisfy the mission requirements and optimize the deployment process. However, in certain scenarios, Two-hop COVER may not achieve full demand satisfaction. Therefore, the second stage, called Trace Fingerprint is invoked to guarantee full satisfaction. Finally, a fairness-aware version of Two-hop COVER is presented to consider scenarios in which the mission requirements are greater than the available resources (i.e. robots) and hence, the fairness-aware approach dispatches robots in proportion to each landmark's need. Extensive simulation experiments have been carried out to assess the performance of the proposed framework. The simulation results demonstrate the effectiveness of the proposed approaches considering several performance factors, such as total travelled distance, total exchanged messages, total deployment time, and Jain's fairness index.

Suggested Citation

  • Sallam, Gamal & Baroudi, Uthman, 2020. "A two-stage framework for fair autonomous robot deployment using virtual forces," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 35-50.
  • Handle: RePEc:eee:transa:v:141:y:2020:i:c:p:35-50
    DOI: 10.1016/j.tra.2020.08.009
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    References listed on IDEAS

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    1. Sheehan, Barry & Murphy, Finbarr & Mullins, Martin & Ryan, Cian, 2019. "Connected and autonomous vehicles: A cyber-risk classification framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 523-536.
    2. Fagnant, Daniel J. & Kockelman, Kara, 2015. "Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 167-181.
    3. H. W. Kuhn, 1955. "The Hungarian method for the assignment problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 83-97, March.
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