Graph Structure-Based Simultaneous Localization and Mapping Using a Hybrid Method of 2D Laser Scan and Monocular Camera Image in Environments with Laser Scan Ambiguity.
Graph Structure-Based Simultaneous Localization and Mapping Using a Hybrid Method of 2D Laser Scan and Monocular Camera Image in Environments with Laser Scan Ambiguity.
复制标题
在激光扫描模棱两可的环境中，使用2D激光扫描和单眼相机图像的混合方法基于图结构的同时定位和映射。
DOI：
10.3390/s150715830
复制
发表时间：
2015-07-03
期刊：
影响因子：
--
通讯作者：
Myung H
中科院分区：
文献类型：
--
作者：
Oh T;Lee D;Kim H;Myung H
定位是机器人导航的一个基本问题，允许机器人自主执行任务。然而，在具有激光扫描模糊性的环境中，诸如长走廊，利用激光扫描仪的传统SLAM（同时定位和映射）算法可能不能鲁棒地估计机器人姿态。为了解决这个问题，我们提出了一种新的定位方法的基础上的混合方法，将一个二维激光扫描仪和一个单目摄像机的框架内，基于图形结构的SLAM。在假设墙体垂直于地面且垂直平坦的条件下，通过混合方法获取图像特征点的三维坐标。然而，这种假设可以被解除，因为随后的特征匹配过程拒绝了倾斜或非平坦壁上的离群值。通过图优化与混合方法产生的约束，最终机器人位姿估计。为了验证该方法的有效性，在室内长走廊环境中进行了真实的实验。实验结果与传统的GMapping方法进行了比较。实验结果表明，该方法能够在激光扫描模糊的环境中实现机器人的真实的实时定位，且定位性能优于传统方法，具有上级的优点。
Localization is an essential issue for robot navigation, allowing the robot to perform tasks autonomously. However, in environments with laser scan ambiguity, such as long corridors, the conventional SLAM (simultaneous localization and mapping) algorithms exploiting a laser scanner may not estimate the robot pose robustly. To resolve this problem, we propose a novel localization approach based on a hybrid method incorporating a 2D laser scanner and a monocular camera in the framework of a graph structure-based SLAM. 3D coordinates of image feature points are acquired through the hybrid method, with the assumption that the wall is normal to the ground and vertically flat. However, this assumption can be relieved, because the subsequent feature matching process rejects the outliers on an inclined or non-flat wall. Through graph optimization with constraints generated by the hybrid method, the final robot pose is estimated. To verify the effectiveness of the proposed method, real experiments were conducted in an indoor environment with a long corridor. The experimental results were compared with those of the conventional GMappingapproach. The results demonstrate that it is possible to localize the robot in environments with laser scan ambiguity in real time, and the performance of the proposed method is superior to that of the conventional approach.