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Random networks in configuration space for fast path planning.

机译:配置空间中的随机网络,用于快速路径规划。

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In the main part of this dissertation we present a new path planning method which computes collision-free paths for robots of virtually any type moving among stationary obstacles. This method proceeds according to two phases: a preprocessing phase and a query phase. In the preprocessing phase, a probabilistic network is constructed and stored as a graph whose nodes correspond to collision-free configurations and edges to feasible paths between these configurations. These paths are computed using a fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the network; the network is then searched for a path joining these two nodes. The method is general and easy to implement. Increased efficiency can be achieved by tailoring some of its components (e.g. the local planner) to the considered robots. We apply the method to articulated robots with many degrees of freedom. Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation ({dollar}approx{dollar}150 MIPS), after relatively short preprocessing times (a few dozen to a few hundred seconds).; In the second part of this dissertation, we present a new method for computing the obstacle map used in motion planning algorithms. The method computes a convolution of the workspace and the robot using the Fast Fourier Transform (FFT). It is particularly promising for workspaces with many and/or complicated obstacles. Furthermore, it is an inherently parallel method that can significantly benefit from existing experience and hardware on the FFT.; In the third part of this dissertation, we consider a problem from assembly planning. In assembly planning we are interested in generating feasible sequences of motions that construct a mechanical product from its individual parts. The problem addressed is the following: given a planar assembly of polygons, decide if there is a proper subcollection of them that can be removed as a rigid body without colliding with or disturbing the other parts of the assembly. We prove that this problem is NP-complete. The result extends to several interesting variants of the problem.
机译:在本文的主要部分,我们提出了一种新的路径规划方法,该方法可以计算几乎任何类型的机器人在固定障碍物之间移动的无碰撞路径。该方法根据两个阶段进行:预处理阶段和查询阶段。在预处理阶段,概率网络被构建并存储为图形,其节点对应于无冲突配置,并且边缘对应于这些配置之间的可行路径。这些路径是使用快速本地计划程序计算的。在查询阶段,机器人的任何给定的开始和目标配置都连接到网络的两个节点。然后在网络中搜索连接这两个节点的路径。该方法通用且易于实现。通过针对考虑的机器人量身定制某些组件(例如本地计划员),可以提高效率。我们将该方法应用于具有许多自由度的铰接式机器人。实验结果表明,在相对较短的预处理时间(几十到几百秒)之后,就可以在当代工作站({dollar}约{dollar} 150 MIPS)上不到一秒钟的时间完成路径规划。在本文的第二部分,我们提出了一种新的计算运动规划算法中障碍物图的方法。该方法使用快速傅立叶变换(FFT)计算工作空间和机器人的卷积。对于具有许多和/或复杂障碍物的工作空间来说,这是特别有希望的。此外,它是一种固有的并行方法,可以从FFT的现有经验和硬件中受益匪浅。在本文的第三部分,我们从装配计划中考虑了一个问题。在装配计划中,我们对生成可行的运动序列感兴趣,这些运动序列是由各个零件构成机械产品的。解决的问题如下:给定平面的多边形组合,确定是否有适当的子集合可以作为刚体移除,而不会碰撞或干扰该集合的其他部分。我们证明这个问题是NP完全的。结果扩展到该问题的几个有趣的变体。

著录项

  • 作者

    Kavraki, Lydia E.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 1995
  • 页码 147 p.
  • 总页数 147
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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