On actively closing loops in grid-based FastSLAM
On actively closing loops in grid-based FastSLAM
复制标题
基于网格的 FastSLAM 中的主动闭环
DOI：
10.1163/156855305774662181
复制
发表时间：
2005
影响因子：
2
通讯作者：
G. Grisetti
中科院分区：
文献类型：
--
作者：
C. Stachniss;D. Hähnel;Wolfram Burgard;G. Grisetti
获取环境模型属于移动机器人的基本任务。过去，一些研究人员主要关注同步定位与建图（SLAM）问题。经典 SLAM 方法是被动的，因为它们仅处理感知的传感器数据，不影响移动机器人的运动。在本文中，我们提出了一种新颖的集成方法，将自主探索与同步定位和映射相结合。我们的方法使用基于网格的 FastSLAM 算法版本，并在每个时间点考虑在探索过程中主动闭环的操作。通过重新进入已经访问过的区域，机器人可以减少其定位误差，从而学习更准确的地图。本文提出的实验结果说明了我们的方法相对于以前缺乏主动闭环能力的方法的优势。
Acquiring models of the environment belongs to the fundamental tasks of mobile robots. In the past, several researchers have focused on the problem of simultaneous localization and mapping (SLAM). Classical SLAM approaches are passive in the sense that they only process the perceived sensor data and do not influence the motion of the mobile robot. In this paper, we present a novel integrated approach that combines autonomous exploration with simultaneous localization and mapping. Our method uses a grid-based version of the FastSLAM algorithm and considers at each point in time actions to actively close loops during exploration. By re-entering already visited areas, the robot reduces its localization error and in this way learns more accurate maps. Experimental results presented in this paper illustrate the advantage of our method over previous approaches that lack the ability to actively close loops.