摘要
This study addresses the problem of maximizing the task-assignment reward of a fleet of heterogeneous autonomous aerial vehicles (AAVs) in a dynamic reconnaissance and confirmation task in uncertain scenarios and multi-AAV tasks, where the coupled path optimization objectives need to be considered. The existing consensus-based bundle algorithm is extended using an effective method for managing multitask and multiagent constraints. In addition, the Bayesian estimation is adopted to handle uncertainties in a given scenario. The proposed method is verified by the sample run tests on a disaster area reconnaissance and confirmation task. The test results verify both the practicality and advantages of the proposed method. Finally, a robust extension to the consensus-based bundle algorithm that handles coupling with the path planning optimization in dynamic search and rescue scenarios, including tasks with multi-AAV service requirements and time-critical constraints, is introduced.
源语言 | 英语 |
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页(从-至) | 48-60 |
页数 | 13 |
期刊 | IEEE Aerospace and Electronic Systems Magazine |
卷 | 40 |
期 | 3 |
DOI | |
出版状态 | 已出版 - 2025 |