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Generation of dynamically feasible and collision free trajectory by applying six-order Bezier curve and local optimal reshaping

机译:通过应用六阶Bezier曲线和局部最优整形来生成动态可行且无碰撞的轨迹

摘要

This paper considers the problem of generating dynamically feasible and collision free trajectory for unmanned aerial vehicles(UAVs) in cluttered environments. General random-based searching algorithms output piecewise linear paths, which cause big discrepancy when used as navigation reference for UAVs with high speed. Meanwhile, the disturbance may also occur to lead the UAVs into danger. In order to obtain agile autonomy without potential dangers, this paper introduces a three-step method to generate feasible reference. In the first step, a six-order Bezier curve, which uses Tuning Rotation to decrease the curvature, is introduced to smooth the output of the path planner. Then a forward simulation is implemented to find the potential dangerous regions. Finally, the path is reshaped by local optimal reshaping planner to eliminate residual dangers. The three steps form a circulation, the reshaped path sent to the first step again to check dynamic feasibility and safety. The method combining Six-order Bezier curve, Tuning Rotation, and local optimal reshaping is proposed by us for the first time, where the Tuning Rotation is able to meet various curvature requirements without violating the previous path, local optimal reshaping obtains both temporal and spatial reshaping with high time efficiency. The method addresses the system dynamics to achieve agile autonomy, which provides the geometry reference as well as the low level control. The effectiveness of the proposed method is demonstrated by the simulations.
机译:本文考虑了在杂乱环境中为无人机产生动态可行且无碰撞的轨迹的问题。常规的基于随机的搜索算法输出分段线性路径,当用作高速无人机的导航参考时,会导致较大的差异。同时,干扰也可能发生,导致无人机陷入危险。为了获得没有潜在危险的敏捷自治,本文引入了一种三步法来产生可行的参考。第一步,引入六阶贝塞尔曲线,该曲线使用“调整旋转”来减小曲率,以平滑路径规划器的输出。然后实施正向仿真以发现潜在的危险区域。最后,通过局部最佳整形规划器对路径进行整形,以消除残留的危险。这三个步骤形成一个循环,重新设计的路径再次发送到第一步,以检查动态可行性和安全性。我们首次提出了六阶贝塞尔曲线,“调整旋转”和局部最优整形的方法,其中“调整旋转”能够在不违反先前路径的情况下满足各种曲率要求,局部最优整形既获得了时间上的空间优势重塑具有高时间效率。该方法解决了系统动力学问题,以实现敏捷自治,从而提供了几何参考以及低级控制。仿真结果证明了该方法的有效性。

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