SURF (Speeded-Up Robust Features) Based Visual Localization for a Mobile Robot

• Main Authors: Chung-Ying Chen, 陳俊穎
• Other Authors: 林麗章
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/63955133610815789402

碩士 === 國立中興大學 === 機械工程學系所 === 101 === In this thesis, we consider the application of a visual based localization and mapping algorithm for a 4-Mecanum omni-directional mobile robot. Digital images are took by a camera in different time and pose. Using basic image processing technology and Speeded-Up Robust Features (SURF) detector, the coordinates of some feature points in an image are extracted, and the feature points detected in successive different images, projected from the same scene points are then matched. Based on the matched feature points between two successive images and using the Structure-from-Motion (SfM) algorithm, the translation vector and rotation matrix between the poses of camera in different time are calculated. The depths of feature points can then be retrieved in absolute scale with some constraints by using the obtained translation vector and rotation matrix. Finally, the camera attached to mobile robot and object coordinates in the world coordinate frame are found via the translation vector, rotation matrix, and the depths of the feature points. Experimental results are then presented for illustrating the performance of the suggested visual-based localization method.