Soleymani, Seyed Ahmad, Goudarzi, Shidrokh ORCID: https://orcid.org/0000-0003-0383-3553, Liu, Xingchi, Lugovskaya, Lyudmila, Wang, Wenwu and Xiao, Pei (2023) Multi-Target Tracking Using a Swarm of UAVs by Q-learning Algorithm. In: 2023 Sensor Signal Processing for Defence Conference (SSPD), 12-13 September 2023, Edinburgh, United Kingdom.

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Abstract

This paper proposes a scheme for multiple unmanned aerial vehicles (UAVs) to track multiple targets in challenging 3-D environments while avoiding obstacle collisions.
The scheme relies on Received-Signal-Strength-Indicator (RSSI) measurements to estimate and track target positions and uses a Q-Learning (QL) algorithm to enhance the intelligence of UAVs for autonomous navigation and obstacle avoidance. Considering the limitation of UAVs in their power and computing capacity, a global reward function is used to determine the optimal actions for the joint control of energy consumption, computation time, and tracking accuracy. Extensive simulations demonstrate the effectiveness of the proposed scheme, achieving accurate and efficient target tracking with low energy consumption.

Item Type:	Conference or Workshop Item (Paper)
Identifier:	10.1109/SSPD57945.2023.10256967
Identifier:	10.1109/SSPD57945.2023.10256967
Subjects:	Computing
Depositing User:	Shidrokh Goudarzi
Date Deposited:	02 Dec 2024 09:05
Last Modified:	08 Jan 2025 07:21
URI:	https://repository.uwl.ac.uk/id/eprint/12941

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