论文标题
刚性物体的自由空间：笼子，路径不存在和狭窄的通道检测
Free Space of Rigid Objects: Caging, Path Non-Existence, and Narrow Passage Detection
论文作者
论文摘要
在这项工作中，我们建议算法明确构建2D和3D中刚性对象的配置空间的保守估计。我们的方法能够在配置空间中检测到紧凑的路径组件和狭窄的段落，这对于在机器人操作和路径计划中的应用非常重要。此外，正如我们所证明的那样，它们也适用于化学中分子笼的鉴定。我们的算法基于结果的3和6维配置空间的分解，分为对应于配置空间中固定方向的有限样本的切片。我们利用球的双图和方向的均匀网格来近似配置空间。我们进行实验，以评估具有不同几何特征对象的计算效率，从而证明我们的方法适用于不同的对象形状。我们通过计算对象配置空间越来越细的近似值来研究算法的性能。
In this work we propose algorithms to explicitly construct a conservative estimate of the configuration spaces of rigid objects in 2D and 3D. Our approach is able to detect compact path components and narrow passages in configuration space which are important for applications in robotic manipulation and path planning. Moreover, as we demonstrate, they are also applicable to identification of molecular cages in chemistry. Our algorithms are based on a decomposition of the resulting 3 and 6 dimensional configuration spaces into slices corresponding to a finite sample of fixed orientations in configuration space. We utilize dual diagrams of unions of balls and uniform grids of orientations to approximate the configuration space. We carry out experiments to evaluate the computational efficiency on a set of objects with different geometric features thus demonstrating that our approach is applicable to different object shapes. We investigate the performance of our algorithm by computing increasingly fine-grained approximations of the object's configuration space.
