In many situations, the trajectory of an unmanned aerial vehicle (UAV) is very likely to deviate from the initial path generated by a path planning algorithm. This is in fact due to the existence of dynamic constraints of the UAV. In order to reduce the degree of such a deviation, this research introduces a trajectory planning algorithm, the objective of which is to minimize distance while maintaining security. The algorithm first develops preprocess trajectory points by constructing isosceles triangles then, on the basis of a minimum snap trajectory method, it applies a corridor constraint to an optimization objective function, while the deviation evaluation function is established to quantitatively evaluate the deviation distance. A series of experiments were carried out in a simulation environment with a simplified quay crane model. The results show that the proposed method not only optimizes the time and length of the generated trajectory, but also reduces the average deviation distance by 88.7%. Moreover, the generated trajectory can be well tracked by the UAV through qualitative and quantitative analysis. Overall, the experiments show that the proposed method can generate a higher UAV trajectory quality.

中文翻译：

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港口环境中的无人机航迹规划

在许多情况下，无人飞行器（UAV）的轨迹很可能会偏离路径规划算法生成的初始路径。这实际上是由于无人机的动态约束的存在。为了减少这种偏离的程度，本研究引入了一种轨迹规划算法，其目的是在保持安全性的同时最小化距离。该算法首先通过构造等腰三角形来开发预处理轨迹点，然后在最小捕捉轨迹方法的基础上，将通道约束应用于优化目标函数，同时建立偏差评估函数以定量评估偏差距离。在具有简化码头起重机模型的模拟环境中进行了一系列实验。结果表明，该方法不仅优化了生成轨迹的时间和长度，而且平均偏离距离减少了88.7％。此外，无人机可以通过定性和定量分析很好地跟踪生成的轨迹。总体而言，实验表明，该方法可以产生更高的无人机轨迹质量。