首页> 外文学位 >Topological and geometric techniques in graph search-based robot planning.
【24h】

Topological and geometric techniques in graph search-based robot planning.

机译:基于图搜索的机器人规划中的拓扑和几何技术。

获取原文
获取原文并翻译 | 示例

摘要

Search-based techniques have been widely used in robot path planning for finding optimal or close-to-optimal trajectories in configuration spaces. They have the advantages of being complete, optimal (up to the metric induced by the discretization) and efficient (in low dimensional problems), and broadly applicable, even to complex environments. Continuous techniques, on the other hand, that incorporate concepts from differential and algebraic topology and geometry, have the ability to exploit specific structures in the original configuration space and can be used to solve different problems that do not lend themselves to graph-search based techniques. We propose several novel ideas and develop new methodologies that will let us bring these two separate techniques under one umbrella. Using tools from algebraic topology we define differential forms with special properties whose integral reveal topological information about the solution path allowing us to impose topological constraints on the planning problems. Metric information can be used along with search-based techniques for creating Voronoi tessellations in coverage and exploration problems. In particular, we use entropy as a metric for multi-robot exploration and coverage of unknown or partially known non-convex environments. Finally, in multi-robot constrained planning problems we exploit certain special product structure in the high dimensional configuration space that combine the advantages of graph search methods and gradient descent algorithms allowing us to develop powerful tools to solve very high-dimensional planning problems.
机译:基于搜索的技术已广泛用于机器人路径规划中,以在配置空间中找到最佳或接近最佳的轨迹。它们的优点是完整,最优(达到离散化所导致的度量标准)和高效(在低维问题中),并且即使在复杂环境中也具有广泛的适用性。另一方面,连续技术结合了微分,代数拓扑和几何的概念,具有在原始配置空间中利用特定结构的能力,并且可以用于解决不同的问题,这些问题不适合基于图搜索的技术。我们提出了几种新颖的想法并开发了新的方法论,使我们将这两种不同的技术归为一类。使用代数拓扑的工具,我们定义了具有特殊属性的微分形式,这些微分形式的整体揭示了有关求解路径的拓扑信息,从而使我们可以对规划问题施加拓扑约束。度量信息可以与基于搜索的技术一起使用,以在覆盖和勘探问题中创建Voronoi镶嵌。特别是,我们使用熵作为多机器人探索和覆盖未知或部分已知的非凸环境的度量。最后,在多机器人约束规划问题中,我们在高维配置空间中利用某些特殊的产品结构,这些结构结合了图搜索方法和梯度下降算法的优点,从而使我们能够开发强大的工具来解决超高维规划问题。

著录项

  • 作者

    Bhattacharya, Subhrajit.;

  • 作者单位

    University of Pennsylvania.;

  • 授予单位 University of Pennsylvania.;
  • 学科 Engineering Mechanical.;Engineering Robotics.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 191 p.
  • 总页数 191
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号