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Hierarchical path planning of mobile robots in complex indoor environments

机译:复杂室内环境中移动机器人的分层路径规划

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Inspired by the Hierarchical D~(*) (HD~(*)) algorithm of Cagigas (Robotics and Autonomous Systems 52, 190-208, 2005), in this paper we introduce a novel hierarchical path planning algorithm called the Focussed Hierarchical D~(*) (FHD~(*)). Unlike the original HD~(*) algorithm, the FHD~(*) algorithm guarantees the optimality of the global path, and requires considerably less time for the path replanning operations. This is achieved by several modifications: (1) optimal placement of the so-called bridge nodes needed for hierarchy creation, (2) focusing the search around the optimal path, which reduces the search area without loss of optimality, and (3) introduction of partial starts and partial goals, which further reduce computational time of replanning operations. The FHD~(*) algorithm was tested in a multi-room indoor environment and compared with the original HD~(*) algorithm, non-hierarchical D~(*) algorithm, and Focussed D~(*) algorithm under the same conditions. The FHD~(*) algorithm significantly outperforms other algorithms with respect to the computational time. Furthermore, it can be easily extended to the problem of path planning between different floors or buildings.
机译:受Cagigas的Hierarchical D〜(*)(HD〜(*))算法启发(机器人与自治系统52,190-208,2005),本文介绍了一种新颖的分层路径规划算法,称为Focuseded Hierarchical D〜 (*)(FHD〜(*))。与原始的HD〜(*)算法不同,FHD〜(*)算法保证了全局路径的最优性,并且路径重新规划操作所需的时间大大减少。这可以通过以下几种修改来实现:(1)层次结构创建所需的所谓桥节点的最佳放置;(2)将搜索集中在最优路径上,这会在不损失最优性的情况下缩小搜索范围,以及(3)引入部分开始和部分目标,从而进一步减少了重新计划操作的计算时间。在多房间室内环境中对FHD〜(*)算法进行了测试,并与相同条件下的原始HD〜(*)算法,非分层D〜(*)算法和Focussed D〜(*)算法进行了比较。 。就计算时间而言,FHD〜(*)算法明显优于其他算法。此外,它可以容易地扩展到不同楼层或建筑物之间的路径规划问题。

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