Autonomous dispatch trajectory planning of carrier-based vehicles: An iterative safe dispatch corridor framework

作者：Keyan Li, Xin Li, Yu Wu, Zhilong Deng, Yan Wang, Y.R. Fu Y.D. Meng, Bai Li, Xichao Su, Lei Wang, Xinwei Wang · 发表于：Defence Technology · 年份：2025 · DOI：10.1016/j.dt.2025.09.006 · 被引用次数：6 · 研究领域：Robotic Path Planning Algorithms、Advanced Manufacturing and Logistics Optimization、Vehicle Routing Optimization Methods

As carrier aircraft sortie frequency and flight deck operational density increase, autonomous dispatch trajectory planning for carrier-based vehicles demands efficient, safe, and kinematically feasible solutions. This paper presents an Iterative Safe Dispatch Corridor (iSDC) framework, addressing the suboptimality of the traditional SDC method caused by static corridor construction and redundant obstacle exploration. First, a Kinodynamic-Informed-Bidirectional Rapidly-exploring Random Tree Star (KIB-RRT∗) algorithm is proposed for the front-end coarse planning. By integrating bidirectional tree expansion, goal-biased elliptical sampling, and artificial potential field guidance, it reduces unnecessary exploration near concave obstacles and generates kinematically admissible paths. Secondly, the traditional SDC is implemented in an iterative manner, and the obtained trajectory in the current iteration is fed into the next iteration for corridor generation, thus progressively improving the quality of within-corridor constraints. For tractors, a reverse-motion penalty function is incorporated into the back-end optimizer to prioritize forward driving, aligning with mechanical constraints and human operational preferences. Numerical validations on the data of Gerald R. Ford-class carrier demonstrate that the KIB-RRT∗ reduces average computational time by 75% and expansion nodes by 25% compared to conventional RRT∗ algorithms. Meanwhile, the iSDC framework yields more time-efficient...