公开(公告)号：US20160011594A1

公开(公告)日：2016-01-14

申请号：US14521699

申请日：2014-10-23

Applicant: Korea University Research and Business Foundation

Inventor： Woojin CHUNG ,  Hyunsuk LEE

IPC: G05D1/02 ,  G01S17/06 ,  G01C3/08

CPC classification number: G05D1/0231 ,  G01C3/08 ,  G01C7/04 ,  G01S7/4802 ,  G01S17/42 ,  G01S17/936 ,  G05D1/024 ,  G05D1/0274 ,  G05D2201/0209 ,  G06K9/00798 ,  G06K9/6234 ,  Y10S901/01

Abstract: The invention relates to a method for extracting a curb of a road using a laser range finder and a method for localizing of a mobile robot using curb information of a road. The method for extracting the curb of the road using the laser range finder includes extracting a road surface and line segments from scan data of the laser range finder, extracting a plurality of curb candidate line segments among the line segments on the basis of an angle between the road surface and the line segment, extracting a plurality of curb candidates having a plurality of curb properties, wherein each of the plurality of curb candidates is generated by combining the couple of the curb candidate line segments, and applying the plurality of the curb candidates to a Kernel Fisher Discriminant Analysis to extract a final curb.

Abstract translation: 本发明涉及使用激光测距仪提取道路路缘的方法和使用道路路边信息对移动机器人进行本地化的方法。 使用激光测距仪提取道路的路边的方法包括从激光测距仪的扫描数据中提取路面和线段，基于所述线段中的角度提取多个路缘候选线段， 所述路面和所述线段，提取具有多个路缘特性的多个路缘候补，其中，所述多个路缘候选中的每一个通过组合所述路缘候选线段的所述一对来产生，并且施加所述多个路缘候选 到内核​​Fisher判别分析来提取最终路边。

公开(公告)号：US20210103040A1

公开(公告)日：2021-04-08

申请号：US17060710

申请日：2020-10-01

Applicant: Korea University Research and Business Foundation

Inventor： Woojin CHUNG ,  Hyunsuk LEE

IPC: G01S7/497 ,  G01S17/931 ,  G01S17/894

Abstract: An extrinsic calibration method of multiple 3D LiDAR sensors for an autonomous navigation system is proposed, the method including collecting point clouds by each of the multiple 3D LiDAR sensors; extracting multiple target planes corresponding to a plane from the point clouds of each of the 3D LiDAR sensors; by using the target plane of any one of the multiple 3D LiDAR sensors as a reference plane, detecting a corresponding plane from the target planes of each of the remaining of the 3D LiDAR sensors on the basis of a similarity with the reference plane; calculating initial extrinsic parameters for matching between the reference plane and the corresponding plane based on plane parameters of the reference plane and corresponding plane corresponding to each other; and calculating final extrinsic parameters that minimize variance of measurement points for the reference plane and corresponding plane, on the basis of the initial extrinsic parameters.

公开(公告)号：US20220206491A1

公开(公告)日：2022-06-30

申请号：US17564788

申请日：2021-12-29

Applicant: Korea University Research and Business Foundation

Inventor： Woojin CHUNG ,  Hyunsuk LEE

IPC: G05D1/00 ,  G05D1/02 ,  G01S17/931 ,  G01S17/89

Abstract: The present invention relates to a mobile robot for evaluating self-training based traversability comprising: an elevation map generator which generates a grid-cell based elevation map using point cloud data; a feature extractor which extracts a plurality of types of features on each grid cell from the elevation map; a data set generator which generates a labeled data set labeled for training and an unlabeled data set, based on label features set for at least two types of features among the plurality of types of features; and a self-training unit which generates an AI model for evaluating traversability by self-training using the labeled data set and the unlabeled data set. Accordingly, it is possible to create training data which increases training ability and then use the data for the self-training, whereby traversability can be evaluated while achieving navigation safety and efficiency.

公开(公告)号：US20170060132A1

公开(公告)日：2017-03-02

申请号：US15245425

申请日：2016-08-24

Applicant: Korea University Research and Business Foundation

Inventor： Woojin CHUNG ,  Hyunsuk LEE

IPC: G05D1/02 ,  G01V8/12 ,  B60W30/095

Abstract: The invention relates to a method of detecting a floor obstacle using a laser range finder comprising the following steps: (a) generating normal floor characteristic data with regard to a flat normal driving surface having no floor obstacle; (b) registering the normal floor characteristic data on a pre-registered one-class classification method; (c) obtaining sensing value of the laser range finder according to the driving of a mobile robot; (d) generating sensing value-floor characteristic data with respect to the sensing value; and (e) determining whether the sensing value indicates a normal driving surface or a floor obstacle by applying the sensing value-floor characteristic data to the one-class classification method. Therefore, an obstacle including a relatively small floor obstacle existing on the driving path of a mobile robot can be detected more effectively using a laser range finder, thereby providing more stably an area where the mobile robot can travel.

Abstract translation: 本发明涉及一种使用激光测距仪检测地板障碍物的方法，包括以下步骤：（a）产生关于没有地板障碍物的平面正常驾驶表面的正常地板特性数据; （b）预先注册的一类分类方法登记正常楼层特征数据; （c）根据移动机器人的驱动获得激光测距仪的感测值; （d）产生相对于所述感测值的感测值楼层特性数据; 以及（e）通过将感测值楼层特性数据应用于一类分类方法来确定感测值是否指示正常驾驶面或楼层障碍物。 因此，能够使用激光测距装置更有效地检测出存在于移动机器人的驱动路径上的相对较小的楼层障碍物的障碍物，从而更稳定地提供移动机器人能够行进的区域。