| Title |
Performance Analysis of Optimization Method and Filtering Method for Feature-based Monocular Visual SLAM |
| Authors |
전진석(Jin-Seok Jeon) ; 김효중(Hyo-Joong Kim) ; 심덕선(Duk-Sun Shim) |
| DOI |
http://doi.org/10.5370/KIEE.2019.68.1.182 |
| Keywords |
Camera image ; Monocular SLAM ; Feature point ; Optimization ; Kalman filter ; RANSAC |
| Abstract |
Autonomous mobile robots need SLAM (simultaneous localization and mapping) to look for the location and simultaneously to make the map around the location. In order to achieve visual SLAM, it is necessary to form an algorithm that detects and extracts feature points from camera images, and gets the camera pose and 3D points of the features. In this paper, we propose MPROSAC algorithm which combines MSAC and PROSAC, and compare the performance of optimization method and the filtering method for feature-based monocular visual SLAM. Sparse Bundle Adjustment (SBA) is used for the optimization method and the extended Kalman filter is used for the filtering method. |