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Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs

Rekabi-Bana, Fatemeh; Hu, Junyan; Krajník, Tomáš; Arvin, Farshad

Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs Thumbnail


Authors

Tomáš Krajník



Abstract

Area coverage is an important problem in robotics applications, which has been widely used in search and rescue, offshore industrial inspection, and smart agriculture. This paper demonstrates a novel unified robust path planning, optimal trajectory generation, and control architecture for a quadrotor coverage mission. To achieve safe navigation in uncertain working environments containing obstacles, the proposed algorithm applies a modified probabilistic roadmap to generating a connected search graph considering the risk of collision with the obstacles. Furthermore, a recursive node and link generation scheme determines a more efficient search graph without extra complexity to reduce the computational burden during the planning procedure. An optimal three-dimensional trajectory generation is then suggested to connect the optimal discrete path generated by the planning algorithm, and the robust control policy is designed based on the cascade NLH∞ framework. The integrated framework is capable of compensating for the effects of uncertainties and disturbances while accomplishing the area coverage mission. The feasibility, robustness and performance of the proposed framework are evaluated through Monte Carlo simulations, PX4 Software-In-the-Loop test facility, and real-world experiments.

Citation

Rekabi-Bana, F., Hu, J., Krajník, T., & Arvin, F. (2023). Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs. IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/tits.2023.3320049

Journal Article Type Article
Acceptance Date Sep 21, 2023
Online Publication Date Oct 17, 2023
Publication Date 2023
Deposit Date Nov 7, 2023
Publicly Available Date Nov 7, 2023
Journal IEEE Transactions on Intelligent Transportation Systems
Print ISSN 1524-9050
Electronic ISSN 1558-0016
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1109/tits.2023.3320049
Keywords Computer Science Applications; Mechanical Engineering; Automotive Engineering
Public URL https://durham-repository.worktribe.com/output/1899538

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© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.





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