首页> 外文会议>IEEE/RSJ International Conference on Intelligent Robots and Systems;IROS 2009 >Online complete coverage path planning for mobile robots based on linked spiral paths using constrained inverse distance transform
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Online complete coverage path planning for mobile robots based on linked spiral paths using constrained inverse distance transform

机译:基于约束逆距离变换的基于链接螺旋路径的移动机器人在线完整覆盖路径规划

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This paper presents a sensor-based online coverage path planning algorithm guaranteeing a complete coverage of unstructured planar environments by a mobile robot. The proposed complete coverage algorithm abstracts the environment as a union of robot-sized cells and then uses a spiral filling rule. It can be largely classified as an approximate cellular decomposition approach as defined by Choset. In this paper, we first propose a special map coordinate assignment scheme based on active wall-finding using the history of sensor readings, which can drastically reduce the number of turns on the generated coverage path. Next, we develop an efficient path planner to link the simple spiral paths using the constrained inverse distance transform that we introduced the first time. This planner selects the next target cell which is at the minimal path length away from the current cell among the remaining non-contiguous uncovered cells while at the same time, finding the path to this target to save both the memory and time which are important concern in embedded robotics. Experiments on both simulated and real cleaning robots demonstrate the practical efficiency and robustness of the proposed algorithm.
机译:本文提出了一种基于传感器的在线覆盖路径规划算法,该算法可确保移动机器人完全覆盖非结构化平面环境。提出的完全覆盖算法将环境抽象为机器人大小的单元的并集,然后使用螺旋填充规则。可以将其大致归类为Choset定义的近似细胞分解方法。在本文中,我们首先提出一种基于主动墙查找的特殊地图坐标分配方案,该方案使用传感器读数的历史记录,可以显着减少生成的覆盖路径上的匝数。接下来,我们开发一种有效的路径规划器,以使用我们首次引入的约束逆距离变换来链接简单的螺旋路径。该计划者在剩余的非连续未发现单元中选择距离当前单元最小路径长度的下一个目标单元,同时,找到通往该目标的路径以节省内存和时间,这是重要的考虑因素在嵌入式机器人中。在模拟和实际清洁机器人上的实验都证明了该算法的实用效率和鲁棒性。

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