Integrated Consensus Framework for Task Assignment and Path Planning of a Degraded UAV Fleet

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Integrated Consensus Framework for Task Assignment and Path Planning of a Degraded UAV Fleet

Author Information
1
United States Office of Naval Research, 875 N. Randolph St., Arlington, VA 22203, USA
2
Department of Marketing, Southeast Missouri State University, One University Plaza MS 5875, Cape Girardeau, MO 63701, USA
3
Department of Engineering & Technology, Southeast Missouri State University, One University Plaza MS 6825, Cape Girardeau, MO 63701, USA
*
Authors to whom correspondence should be addressed.
Present: Robbins College of Business & Entrepreneurship, Fort Hays State University, 600 Park Street, McCartney Hall 302, Hays, KS 67601, USA.

Received: 28 July 2025 Accepted: 19 September 2025 Published: 28 September 2025

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© 2025 The authors. This is an open access article under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

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Drones Veh. Auton. 2025, 2(4), 10016; DOI: 10.70322/dav.2025.10016
ABSTRACT: Unmanned aerial vehicle (UAV) systems can fail during civil and military operations. This presents a significant challenge for human teleoperators (remote pilots) in determining task reallocation after member loss within the fleet. To alleviate the high cognitive load on teleoperators in critical situations, a decentralized strategy was developed to resolve the combined task assignment and vehicle routing problems. This Integrated Consensus Framework (ICF) not only solves the combined problem but also adds a unique ability to identify the loss of a vehicle and dynamically reroute agents to abandoned tasks to achieve a satisfactory solution. ICF is a two-tiered approach that combines a novel algorithm, the Caravan Auction (CarA) algorithm, with a path-planning strategy to identify when UAVs are lost and reallocate orphaned tasks. The CarA Algorithm consists of three phases: auction, consensus, and validation phases. An experiment using Monte Carlo simulations was conducted to determine the performance of ICF. Teleoperators assigned to complete multiple tasks with UAVs in dangerous environments can allow the proposed system to perform task assignments and reallocation while offering only supervisory control as needed. The results indicate this novel approach provides comparable performance to existing strategies, doing so with the addition of randomized UAV loss.
Keywords: Unmanned aircraft systems; Multi-vehicle intelligent systems; Coordinated control
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