This paper presents modified hybrid A^∗ algorithms to facilitate more efficient path finding around narrow passages under the shape and kinematic constraints of a car-like vehicle. First, we propose spline- and bidirectional-search-based hybrid A^∗ using G² continuous motion primitives with multiple turning radii depending on cubic Bezier curves. In addition, we present a heuristic applying the vector field histogram to find a path around narrow passages with efficiency rather than optimization. We demonstrate the benefits of our method through simulations and experimental results using an autonomous ground vehicle in environments with narrow passages.

本文提出了改进的混合 A ^*算法，以促进在类似汽车的车辆的形状和运动学约束下在狭窄通道周围更有效的路径查找。首先，我们提出了基于样条和双向搜索的混合 A ^*使用 G ²连续运动原语，具有多个取决于三次贝塞尔曲线的转弯半径。此外，我们提出了一种启发式方法，即应用矢量场直方图以高效而非优化的方式找到狭窄通道周围的路径。我们通过在狭窄通道环境中使用自主地面车辆的模拟和实验结果证明了我们方法的好处。