Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151289
Title: 3D path planning and real-time collision resolution of multirotor drone operations in complex urban low-altitude airspace
Authors: Zhang, Na
Zhang, Mingcheng
Low, Kin Huat
Keywords: Engineering::Aeronautical engineering
Issue Date: 2021
Source: Zhang, N., Zhang, M. & Low, K. H. (2021). 3D path planning and real-time collision resolution of multirotor drone operations in complex urban low-altitude airspace. Transportation Research Part C: Emerging Technologies, 129, 103123-. https://dx.doi.org/10.1016/j.trc.2021.103123
Project: 2018-T1-002-124 
Journal: Transportation Research Part C: Emerging Technologies 
Abstract: Drones have been greatly developed to facilitate the progress of various industries. The safe operation of drones in the urban airspace is critical to ensure a reliable and high-efficient urban air traffic system. This work presents a fusion scheme to achieve autonomous drone collision-free path planning considering static obstacles and dynamic threats detected. Firstly, a 3D voxel jump point search (JPS) based path planning model is developed to generate the static collision-free reference path. With the optimization, the reference path is then de-diagonalized, recon- structed, and smoothed to obtain the desired path. Subsequently, a local collision resolution method is proposed to avoid near mid-air collision of the dynamic threats. The method is based on the Markov decision process (MDP) to implement real-time dynamic collision avoidance. Simu- lations are conducted to verify the performance of the proposed model. The simulation results demonstrate that the proposed model is effective to achieve the autonomous path planning and real-time collision resolution of multirotor drones.
URI: https://hdl.handle.net/10356/151289
ISSN: 0968-090X
DOI: 10.1016/j.trc.2021.103123
Rights: © 2021 Elsevier Ltd. All rights reserved. This paper was published in Transportation Research Part C: Emerging Technologies and is made available with permission of Elsevier Ltd.
Fulltext Permission: embargo_20230907
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Journal Articles
MAE Journal Articles

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Accepted Version of Manuscript TRC-D-20-02267R1-newest.pdf
  Until 2023-09-07
2.06 MBAdobe PDFUnder embargo until Sep 07, 2023

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