Multi-target points path planning for fixed-wing unmanned aerial vehicle performing reconnaissance missions

Qingshan Cui

doi:10.1117/12.2689384

10 August 2023 Multi-target points path planning for fixed-wing unmanned aerial vehicle performing reconnaissance missions

Qingshan Cui

Author Affiliations +

Proceedings Volume 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023); 127482W (2023) https://doi.org/10.1117/12.2689384
Event: 5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023), 2023, Wuhan, China

Abstract

In this paper, we study the path planning problem of a fixed-wing unmanned aerial vehicle (UAV) with a reconnaissance camera when performing a reconnaissance mission in airspace containing a no-fly zone. Due to the UAV's dynamic constraints and the reconnaissance mission's specificity, the problem can be formulated as a special variant of the traveling salesman problem (TSP), called the dynamic-constrained TSP with neighborhoods (DCTSPN). To solve this problem, the authors propose a hierarchical algorithm based on deep reinforcement learning (DRL), divided into an optimal sequence planning layer and a shortest path planning layer. In the optimal sequence planning layer, Firstly, the neighborhood boundary of the target point is discretized to form multiple reconnaissance points; then, the complex trajectory planning problem is simplified to planning on a finite directed graph by randomly selecting a finite set of reconnaissance points from the neighborhood boundary of the target point set. The double deep Q network (DDQN) algorithm is used to solve for the target point traversal sequence and the reconnaissance points for each target. In the shortest path planning layer, Use the Deep Deterministic Policy Gradient (DDPG) algorithm to perform global path planning in continuous state space and action space and generate a dynamically feasible optimal flight trajectory under the guidance of the optimal reconnaissance sequence to complete the given reconnaissance mission, Avoid no-fly zones. The simulation results show that the hierarchical algorithm is highly applicable and efficient.

Citation Download Citation

Qingshan Cui "Multi-target points path planning for fixed-wing unmanned aerial vehicle performing reconnaissance missions", Proc. SPIE 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 127482W (10 August 2023); https://doi.org/10.1117/12.2689384

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KEYWORDS

Unmanned aerial vehicles

Reconnaissance

Detection and tracking algorithms

Education and training

Neural networks

Computer simulations

Algorithm development

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