Abstract
The rapid evolution of Unmanned Aerial Vehicles (UAVs) has revolutionized target search operations in various fields, including military applications, search and rescue missions, and post-disaster management. In this paper, we propose the use of a multi-armed bandit algorithm for a UAV's search mission in an unknown and adversarial setting. The UAV's objective is to locate a mobile target formation, assuming that their mobility resembles an adversarial behavior. To achieve this, we formulate an optimization problem and leverage the Exp3 (exponential-weighted exploration and exploitation) algorithm to solve it. The targets are assumed to be moving under the assumption of an unknown and potentially non-stationary probability distribution. To enhance the learning process, we integrate environmental observations as contextual information, resulting in a variant called C-Exp3, which optimizes the search process. Finally, we evaluate the performance of C-Exp3 in UAV search missions, focusing on adversarial environments. The primary objective for the UAV is to converge towards an optimal policy as time t approaches the horizon T, reflecting the UAV's capacity to learn the formation's strategy.
Original language | English |
---|---|
Title of host publication | Proceedings of the 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) |
Publisher | IEEE |
Pages | 753-758 |
Number of pages | 6 |
ISBN (Electronic) | 979-8-3503-7162-8 |
ISBN (Print) | 979-8-3503-7163-5 |
DOIs | |
Publication status | Published - 2024 |
Event | 2024 Annual IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2024 - Kingston, Canada Duration: 6 Aug 2024 → 9 Aug 2024 |
Publication series
Name | Canadian Conference on Electrical and Computer Engineering |
---|---|
ISSN (Print) | 0840-7789 |
Conference
Conference | 2024 Annual IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2024 |
---|---|
Country/Territory | Canada |
City | Kingston |
Period | 6/08/24 → 9/08/24 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Multi-Armed Bandits
- Online Learning
- Search Mission
- UAV