An enhanced occupancy map for exploration via pose separation
An enhanced occupancy map for exploration via pose separation
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通过姿势分离进行探索的增强占用图
DOI：
10.1109/iros.2003.1250712
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
H. Choset
中科院分区：
文献类型：
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作者：
R. Grabowski;P. Khosla;H. Choset
我们开发了一种新的占用地图，该地图尊重传感器测量方位的作用以及它如何与现有占用地图的分辨率相关联。我们借鉴了科诺奇的想法，在一张类似占用的地图上记录和跟踪传感器读数相对于给定细胞的方位。我们的具体贡献在于我们处理传感器姿态信息的方式，当传感器读数指示特定细胞中存在障碍物时，该信息是传感器读数的方位。对于占用图中的每个单元，我们计算关联姿势的最大间隔，然后将该信息存储在称为姿势图的新的二维数组中。姿势图中的单元格测量占用图的相应单元格中包含的信息质量。我们将新的姿势贴图与现有的贴图合并，以生成增强的占用贴图。从增强的占用地图导出的探测计划更有效和完整，因为它们不引导机器人绕过幻影障碍物，也不会错误地将狭窄的开口分类为在传统占用地图中常见的闭合。
We develop a new occupancy map that respects the role of the sensor measurement bearing and how it relates to the resolution of the existing occupancy map. We borrow an idea from Konolige for recording and tracking, in an occupancy-like map, the bearing at which sensor readings originate with respect to a given cell. Our specific contribution is in the way we process the sensor pose information, which is the bearing of the sensor readings when it indicates the presence of an obstacle in a particular cell. For each cell in the occupancy map, we calculate the greatest separation of incident poses, and then store that information in a new two-dimensional array called a pose map. A cell in the pose map measures the quality of information contained in the corresponding cell of the occupancy map. We merge the new pose map with the existing map to generate an enhanced occupancy map. Exploration plans derived from the enhanced occupancy map are more efficient and complete in that they do not guide the robot around phantom obstacles nor incorrectly classify narrow openings as closed commonly found in conventional occupancy maps.