3D path planning and real-time collision resolution of multirotor drone operations in complex urban low-altitude airspace. (August 2021)

• Record Type: Journal Article
• Authors: Zhang, Na; Zhang, Mingcheng; Low, Kin Huat
• Is Part Of: Transportation research. Volume 129(2021)
• Publication Date: 2021-08
• Subjects: Static obstacles -- Dynamic threats -- Near mid-air collision avoidance -- 3D voxel jump point search -- Markov decision process; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2021.103123
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Developed 3D voxel jump point search to plan static global collision-free paths. Proposed techniques of de-diagonalization, reconstruction, and smoothness. Introduced the discrete-time MDP-based dynamic collision resolution scheme. 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, reconstructed, 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. Simulations 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.