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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV)

Almadhoun, Randa, Taha, Tarek, Dias, Jorge, Seneviratne, Lakmal and Zweiri, Yahya (2019) Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV). Lecture Notes in Computer Science, 11744. pp. 243-266. ISSN 0302-9743

Item Type: Article


The most critical process in the inspection is the structure coverage which is a time and resource intensive task. In this paper, Search Space Coverage Path Planning (SSCPP) algorithm for inspecting complex structure using a vehicular system consisting of Unmanned Aerial Vehicle (UAV) is proposed. The proposed algorithm exploits our knowledge of the structure model, and the UAV’s onboard sensors to generate coverage paths that maximizes coverage and accuracy. The algorithm supports the integration of multiple sensors to increase the coverage at each viewpoint and reduce the mission time. A weighted heuristic reward function is developed in the algorithm to target coverage, accuracy, travelled distance and turning angle at each viewpoint. The iterative processes of the proposed algorithm were accelerated exploiting the parallel architecture of the Graphics Processing Unit (GPU). A set of experiments using models of different shapes were conducted in simulated and real environments. The simulation and experimental results show the validity and effectiveness of the proposed algorithm.

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More Information

Depositing User: Randa Almadhoun


Item ID: 16460
Identification Number:
ISSN: 0302-9743
Official URL:

Users with ORCIDS

ORCID for Randa Almadhoun: ORCID iD
ORCID for Tarek Taha: ORCID iD
ORCID for Jorge Dias: ORCID iD
ORCID for Lakmal Seneviratne: ORCID iD
ORCID for Yahya Zweiri: ORCID iD

Catalogue record

Date Deposited: 20 Nov 2023 10:38
Last Modified: 20 Nov 2023 10:38


Author: Randa Almadhoun ORCID iD
Author: Tarek Taha ORCID iD
Author: Jorge Dias ORCID iD
Author: Lakmal Seneviratne ORCID iD
Author: Yahya Zweiri ORCID iD

University Divisions

Faculty of Technology


Computing > Artificial Intelligence

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