Autonomous dispatch trajectory planning on flight deck: A search-resampling-optimization framework. (March 2023)

• Record Type: Journal Article
• Authors: Wang, Xinwei; Li, Bai; Su, Xichao; Peng, Haijun; Wang, Lei; Lu, Chen; Wang, Chao
• Is Part Of: Engineering applications of artificial intelligence. Volume 119(2023)
• Publication Date: 2023-03
• Subjects: Aircraft carrier -- Autonomous dispatch -- Trajectory planning -- Optimal control -- Safe dispatch corridor; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2022.105792
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: There is a growing expectation to realize the autonomous dispatch on flight deck, where dispatch trajectory planning is seen as the key technique. Optimal-control based method has shown great advantages in high degree of constraint satisfaction over its counterparts in the last decade. However, it suffers from low computational efficiency even numerical divergence under scenarios with complicated obstacles. To deal with such an issue, a search-resampling-optimization (SRO) framework is proposed in this paper. A hybrid A* algorithm is employed to generate a coarse path according to the boundary conditions in the search stage. Then a resampling process is implemented to pave a series of safe dispatch corridors (SDCs) along the coarse path. Finally, by replacing the common one-to-one collision-avoidance with the constructed within-SDC constraints, an optimal control problem whose scale is totally independent of the number of obstacles can be formulated. The resampled result is further fed into the optimization stage to facilitate the numerical solution. Dispatch trajectory planning for taxiing aircraft and tractor can be treated uniformly under this framework. And numerical simulations demonstrate that the SRO framework is efficient and robust even with narrow accessible tunnels. The SRO is inherently flexible and can be easily extended to the trajectory planning problem in other fields. A video of the main idea and numerical simulations in this paper is available at www.bilibili.com/video/BV1tP4y1d7xy/ .