Fixed-wing unmanned aerial vehicles (UAVs) are frequently confronted with no-fly zones during mission execution, expecting the path planning to be performed under airspace constraints to meet designated requirement. In this study, a smooth path planning method based on the geometric properties of no-fly zones is proposed. It formulates the UAV flight path as a smooth combination of line segments and circular arcs, and models no-fly zones as circular or polygonal regions. By excavating the unique geometric properties of no-fly zones, intersections between the planned path and the no-fly zones can be efficiently detected, thereby reducing computational complexity and improving the accuracy of the generated path. This approach mitigates excessive conservativeness and significantly decreases the number of branches conditional checks. The resulting optimization problem is formulated as a nonlinear programming and solved using the Sequential Quadratic Programming (SQP) method. To evaluate the performance, simulations are conducted on both a desktop computer and an embedded demo board, followed by real-world validation on an unmanned platform. Experimental results demonstrate that the proposed algorithm exhibits remarkable adaptability and high execution efficiency.
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