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首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >A New Cell-subdivision Approach to Plan Free Translations in Cluttered Environments
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A New Cell-subdivision Approach to Plan Free Translations in Cluttered Environments

机译:一种在杂乱环境中计划自由翻译的新单元细分方法

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摘要

This paper presents a thorough discussion of the potential of a new cell-subdivision approach to plan translations of a convex polygon in a cluttered environment, where the focus is on planning simple motions on the basis of a fine-grained description of the workspace, A free path is planned in two main stages. The first stage exploits a plane-sweep paradigm in order to build a cell subdivision holding much relevant topological information on the free space and organizing a set of polygonal chains that approximate the boundaries of the configuration space obstacles. Then, the computations in the second stage are driven by an A{sup}* scheme designed to search the cell subdivision. During the search the bounding chains are subject to further refinements, but the cell graph is no longer modified. Among the remarkable features of the proposed technique we can mention: simple interface with the geometric modeler, based on two collision-detection primitives; small number of cells and adjacencies; incremental characterization of the free space. A few numerical results suggest that the new technique should be worth considering for applications, where appropriate; in particular, it seems to perform better than other approaches based on quadtrees. Moreover, it is quite interesting to observe that the cost of finding collision-free paths grows with the number of convex obstacles, whereas it is almost independent of the overall number of sides: we can interpret this result as supporting the choice of representing the obstacles decomposed into convex components. A succinct comparison between algorithmic and human intuitive path planning is also discussed in order to appraise the rate of redundant information processed by the algorithm, but we can also see that human planners behave significantly better only when the solutions are easy to find.
机译:本文全面讨论了一种新的单元细分方法在杂乱环境中计划凸多边形平移的潜力,该方法的重点是在对工作空间A进行细粒度描述的基础上计划简单的运动自由道路计划分为两个主要阶段。第一阶段利用平面扫描范例,以建立一个单元细分,在自由空间上保存大量相关的拓扑信息,并组织一组近似于配置空间障碍物边界的多边形链。然后,第二阶段的计算由旨在搜索单元细分的A {sup} *方案驱动。在搜索过程中,对边界链进行进一步细化,但不再修改单元格图。在提出的技术的显着特征中,我们可以提到:与几何建模器的简单接口,基于两个碰撞检测原语;单元和邻接的数量很少;可用空间的增量表征。一些数值结果表明,在适当的情况下,该新技术应值得考虑应用。特别是,它似乎比其他基于四叉树的方法表现更好。此外,非常有趣的是,发现无碰撞路径的成本随凸出障碍物的数量而增加,而这几乎与侧面总数无关:我们可以将此结果解释为支持代表障碍物的选择分解为凸分量。为了评估算法处理的冗余信息的比率,还讨论了算法与人类直观路径规划之间的简洁比较,但是我们还可以看到,只有在容易找到解决方案的情况下,人类规划者的行为才能明显改善。

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