论文标题
R2：使用懒惰搜索的基于启发式错误的任何角度路径计划
R2: Heuristic Bug-Based Any-angle Path-Planning using Lazy Searches
论文作者
论文摘要
R2是一种新颖的在线任何角度路径计划者，它使用基于启发式错误或射线铸造方法在具有非凸线，多边形障碍物的2D地图中找到最佳路径。 R2与传统的自由空间计划者具有竞争力，如果查询具有直接视线，请迅速找到路径。在很少有障碍轮廓的大稀疏地图上，在实践中可能会发生的障碍物轮廓，R2的表现要优于自由空间规划师，并且可能比最先进的自由空间扩展计划者Anya快得多。在带有许多轮廓的地图上，ANYA的性能比R2快。 R2建立在Rayscan上，引入了懒惰搜索和源 - 路边计数器，以在连续的轮廓上乐观地找到继任者。这种新颖的方法绕过了锯齿状轮廓上的大多数继任者，以减少昂贵的视线检查，因此不需要预处理才能成为在线竞争性的任何角度策划者。
R2 is a novel online any-angle path planner that uses heuristic bug-based or ray casting approaches to find optimal paths in 2D maps with non-convex, polygonal obstacles. R2 is competitive to traditional free-space planners, finding paths quickly if queries have direct line-of-sight. On large sparse maps with few obstacle contours, which are likely to occur in practice, R2 outperforms free-space planners, and can be much faster than state-of-the-art free-space expansion planner Anya. On maps with many contours, Anya performs faster than R2. R2 is built on RayScan, introducing lazy-searches and a source-pledge counter to find successors optimistically on contiguous contours. The novel approach bypasses most successors on jagged contours to reduce expensive line-of-sight checks, therefore requiring no pre-processing to be a competitive online any-angle planner.
