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Visual place recognition has been vastly researched in the last decade. Most of the previous works have concentrated on improvement of performance when the environment changes due to illumination, weather or season at outdoor with abundant features and textures for place recognition. On the other hand, when a robot moves in a home environment, input images sometimes contain less features or textures...
Recently, RGB-D camera has been used widely in indoor SLAM (Simultaneous Localization and Mapping) field. In this paper, we propose an efficient 3D mapping algorithm that considers appearance of dynamic objects. A full 3D mapping system estimates 6-DoF sensor pose and builds 3D voxel grid map simultaneously. In order to build a 3D map, effective method is proposed in terms of computation time. Depending...
This study was undertaken to create an indoor environmental map using a monocular camera based on structure from motion (SfM). Numerous methods on simultaneous localization and mapping (SLAM) have been proposed for 3D map construction used for various types of mobile robots. We used MonoSLAM proposed by Davidson et al., which is a fundamental method using extended Kalman filters (EKFs) for feature...
In this study, we propose a method to extract features for graph SLAM using an upward-looking camera mounted in an automated guided vehicle (AGV) in a factory environment. To this end, a novel feature detector and descriptor GALS (geometrical arrangement based on lamps and SURF) is proposed in this study. This algorithm consists of two parts: 1) geometrical arrangement of SURF features around a lamp...
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