In order to solve the problem of aircraft deck path planning, based on the elliptic sampling of informed rapidly-exploring random tree (Informed-RRT *), an informed normal-RRT * (IN-RRT *) algorithm using normal distribution sampling was proposed. Firstly, the carrier-based aircraft and the motion scene were modeled, the motion constraints and obstacle avoidance strategies of the carrier-based aircraft were defined, then the normally distributed sampling strategy was combined with elliptic sampling to obtain high-quality and efficient sampling points, the artificial potential field method was introduced to adaptively adjust the search step value of the random tree, the centripetal Catmull-Rom spline interpolation method was used to smooth and optimize the path, and the dynamic window method improved for dynamic obstacles was proposed to realize local dynamic obstacle avoidance. Finally, the performance of the algorithm was tested by experiments in the flat environment of the deck. The results show that the IN-RRT * algorithm can significantly optimize the search time and search path quality, and can plan a reasonable and feasible smooth path for dynamic scenes.