To address the issues of path roughness, low search efficiency, and the difficulty of simultaneously considering Ackermann vehicle kinematic constraints in practical path planning, this study developed a coordinated global–local path planning framework tailored for Ackermann-steered robots. In the global planning stage, a bidirectional A* search framework was enhanced with a dynamic heuristic function, improving the geometric quality of the global path while maintaining search efficiency. Path smoothing was applied to further align the path with Ackermann kinematic constraints. In the local planning stage, the Timed Elastic Band (TEB) algorithm was adapted for Ackermann steering by incorporating minimum turning radius and steering-related constraints, ensuring that the generated trajectories were both collision-free and executable. Python-based simulations on constructed maps were used to compare different heuristic strategies in terms of path length and search efficiency. Results showed that the proposed global planning strategy reduced path length by 34.62% compared with the traditional bidirectional A* algorithm and improved search efficiency by approximately 2.1%. Furthermore, Robot Operating System (ROS) simulations and real-robot tests were conducted to analyze curvature characteristics, velocity variations, and path-tracking performance under different global–local planning combinations. The experimental results demonstrated that the proposed planning framework offered strong engineering practicality and provided a feasible solution for real-world Ackermann-steered robots.

Butterflies are excellent fliers in nature, flapping mode, which can ensure the completion of complex flight movements, including rapid turns, hovering, and forward and backward flights. In this paper, the Chinese yellow swallowtail (Papilio xuthus) was chosen as the bionic research subject. The flapping motion and trajectory function of P. xuthus during takeoff were obtained by the high-speed camera. On this basis, a finite element model of butterfly forewings was established, the flapping trajectory function was imported, and the transient takeoff motion of forewing was simulated by Ansys Fluent 2021R2. The aerodynamic characteristics at different angles of attack during the takeoff were obtained. The flow structure characteristics of the forewing of P. xuthus were analyzed by SIMULIA XFlow 2020. It shows that the lift and drag coefficient of the forewings during takeoff both exhibit a trend of increasing first and then decreasing as the angle of attack increases. The maximum average lift-to-drag ratio is achieved, when the angle of attack is 20°. The obtained wingtip trajectory, optimal angle of attack, and vorticity parameters can provide new design ideas for solving problems such as insufficient takeoff capability and difficult mode switching of flapping-wing microair vehicles design.