4.6 Article

On Hierarchical Multi-UAV Dubins Traveling Salesman Problem Paths in a Complex Obstacle Environment

Journal

IEEE TRANSACTIONS ON CYBERNETICS
Volume -, Issue -, Pages -

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2023.3265926

Keywords

Task analysis; Turning; Heuristic algorithms; Collision avoidance; Clustering algorithms; Nonhomogeneous media; Vehicle dynamics; Bundling ant colony system (BACS); hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP); homotopic adaptive window probabilistic roadmap (AWPRM); obstacle avoidance

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This article addresses a hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP) and proposes approaches for optimal hierarchical coverage and multi-UAV collaboration in a 3-D complex obstacle environment. The proposed strategies include a multi-UAV multilayer projection clustering algorithm, a straight-line flight judgment, and an improved adaptive window probabilistic roadmap algorithm. The sequencing-bundling-bridging framework is used to solve the TSP with obstacles constraints. Simulation experiments demonstrate the feasibility of the proposed strategies in complex obstacle environments for HMDTSP.
This article aims to solve a hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP). Optimal hierarchical coverage and multi-UAV collaboration are achieved by the proposed approaches in a 3-D complex obstacle environment. A multi-UAV multilayer projection clustering (MMPC) algorithm is presented to reduce the cumulative distance from multilayer targets to corresponding cluster centers. A straight-line flight judgment (SFJ) was developed to reduce the calculation of obstacle avoidance. An improved adaptive window probabilistic roadmap (AWPRM) algorithm is addressed to plan obstacle-avoidance paths. The AWPRM improves the feasibility of finding the optimal sequence based on the proposed SFJ compared with a traditional probabilistic roadmap. To solve the solution to TSP with obstacles constraints, the proposed sequencing-bundling-bridging (SBB) framework combines the bundling ant colony system (BACS) and homotopic AWPRM. An obstacle-avoidance optimal curved path is constructed with a turning radius constraint based on the Dubins method and followed up by solving the TSP sequence. The results of simulation experiments indicated that the proposed strategies can provide a set of feasible solutions for HMDTSPs in a complex obstacle environment.

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