An Event-Triggered Path-Based Bid Assignment Method for Energy-Aware Dynamic Multi-UAV Task Allocation

This study addresses dynamic multi-UAV task allocation under online task release, static obstacles, deadlines, limited energy, and vehicle failures. We propose an event-triggered path-based bid assignment method (ET-PBBA). At each mission event, an A-star module estimates the static-obstacle travel cost of feasible UAV–task pairs, while a normalized score combines reward, path length, predicted energy, and secondary load–energy pressure. A one-pass sorted scan then produces an event-local one-to-one assignment. Paired-seed mechanism tests show that event-time activation raises completion rate by 0.046 in the main scenario and 0.065 under failure stress relative to 10 s periodic allocation. The path-dependent physical-cost block provides the dominant improvement over reward-only ranking, whereas the balance term is not significant in the ordinary scenarios. For 10 UAVs and 50 tasks, ET-PBBA reduces average completion time by 5.2% and 4.1% and total energy by 4.3% and 3.0% relative to auction and CBBA, respectively, although Hungarian remains the stronger centralized reference. Under failure stress, completion reaches 0.790 and deadline violations decrease to 9.73. Single-UAV replay completes all 50 nominal waypoints with 9.16 cm mean error, providing auxiliary tracking evidence rather than validation of nonlinear or online multi-UAV execution.

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Publication Details

Journal
Drones
Published
2026-09-09
DOI
https://doi.org/10.3390/drones10090684
Primary Topic
UAV Applications and Optimization
Type
article
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An Event-Triggered Path-Based Bid Assignment Method for Energy-Aware Dynamic Multi-UAV Task Allocation

Xian Zhu, Yuhua Cong, Yujia Li, Zhisheng Wang
Drones
UAV Applications and Optimization
article

An Event-Triggered Path-Based Bid Assignment Method for Energy-Aware Dynamic Multi-UAV Task Allocation

Xian Zhu, Yuhua Cong, Yujia Li, Zhisheng Wang
article en

Abstract

This study addresses dynamic multi-UAV task allocation under online task release, static obstacles, deadlines, limited energy, and vehicle failures. We propose an event-triggered path-based bid assignment method (ET-PBBA). At each mission event, an A-star module estimates the static-obstacle travel cost of feasible UAV–task pairs, while a normalized score combines reward, path length, predicted energy, and secondary load–energy pressure. A one-pass sorted scan then produces an event-local one-to-one assignment. Paired-seed mechanism tests show that event-time activation raises completion rate by 0.046 in the main scenario and 0.065 under failure stress relative to 10 s periodic allocation. The path-dependent physical-cost block provides the dominant improvement over reward-only ranking, whereas the balance term is not significant in the ordinary scenarios. For 10 UAVs and 50 tasks, ET-PBBA reduces average completion time by 5.2% and 4.1% and total energy by 4.3% and 3.0% relative to auction and CBBA, respectively, although Hungarian remains the stronger centralized reference. Under failure stress, completion reaches 0.790 and deadline violations decrease to 9.73. Single-UAV replay completes all 50 nominal waypoints with 9.16 cm mean error, providing auxiliary tracking evidence rather than validation of nonlinear or online multi-UAV execution.

DronesVol. 10(9)
Commercial Aircraft Corporation of China (China) (CN), Nanjing Polytechnic Institute (CN), Nanjing University of Aeronautics and Astronautics (CN)
Affordable and clean energy
Openalex Percentile: Top 7%
UAV Applications and Optimization
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An Event-Triggered Path-Based Bid Assignment Method for Energy-Aware Dynamic Multi-UAV Task Allocation — Xian Zhu, Yuhua Cong, et al. · Drones (2026) | TGRS Research Map | TGRS