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

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 trajectories for both carrier aircraft and tractors, with the dispatch time reduced by 31.3% and tractor reverse motion proportion decreased by 23.4% relative to traditional SDC. The presented framework offers a scalable solution for autonomous dispatch in confined and safety-critical environment, and an illustrative animation is available at bilibili.com/video/BV1tZ7Zz6Eyz. Moreover, the framework can be easily extended to three-dimension scenarios, and thus applicable for trajectory planning of aerial and underwater vehicles.