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Topological Map Building and Exploration Based on Concave Nodes
Howon Cheong,Soonyong Park,Sung-Kee Park 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
This paper addresses the problem of topological mapping and exploration of unknown environments for mobile robot. The topological map is constructed by defining the spatial relationship between adjacent nodes and each node that has geometric information about its circumference. A laser range finder is used as the major sensing modality to collect the geometric data. The node point is extracted from the data in two stages: image-based skeletonization and node point decision. The geometric data are transformed into a skeleton image and the node point is determined among the branch points in the image. We adopt an image processing method to skeletonize the geometric data. The key problem of the topological exploration is to determine the target node among the current node’s neighboring nodes. We also propose an efficient target node decision algorithm based on a concept of concave node. An experiment shows that our approach can explore indoor environments more efficiently.
DaHOG-based Mobile Robot Indoor Global Localization
Howon Cheong,Euntai Kim,Sung-Kee Park 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
This paper suggests an indoor environment descriptor and global localization strategies for indoor robot navigation using a metric sensor and mono camera. Other researches use various feature descriptors (i.e. geometric features, visual local invariant features, and objects) for robot pose estimation. However, most of the real environments have repeated similar texture patterns or few objects although they need salient information for successful localization. To overcome this problem, we suggest a new environment descriptor, which is composed of the histogram of oriented gradient(HOG) and approximated 2D-polar coordinate distance of visual vertical edges. We call it Distance-assisted HOG (DaHOG). For the matching process, we use the omnidirectional datasets that have a circular pattern matching problem. Here, we solve the problem by proposing a new global localization method based on a spectral matching technique. We show that our method is effective with experiments in real environments where there is a lack of distinctive features and objects.
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정호원(Howon Cheong),박순용(Soonyong Park),박민용(Mignon Park),박성기(Sung-Kee Park) 대한전자공학회 2007 대한전자공학회 학술대회 Vol.2007 No.7
This paper presents a new object entity based global localization method with the stereo camera. The map we use here is a hybrid map of global topological map and local object location map. The localization process is divided into two stages coarse pose estimation and refined pose estimation. The coarse pose is computed by using the object recognition and point cloud fitting. And the refined pose is estimated with particle filtering algorithm.