Laser Image SLAM based on Image Matching for Navigation of a Mobile Robot
| Autor: | Jung Won Choi, Yun Won Choi, Kyung Dong Kim, Suk Gyu Lee |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Laser scanning
business.industry Computer science Mechanical Engineering ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Mobile robot Simultaneous localization and mapping Laser Industrial and Manufacturing Engineering law.invention Computer Science::Robotics Extended Kalman filter law Robot Computer vision Artificial intelligence Safety Risk Reliability and Quality business Encoder Backlash |
| Zdroj: | Journal of the Korean Society of Precision Engineering. 30:177-184 |
| ISSN: | 1225-9071 |
| DOI: | 10.7736/kspe.2013.30.2.177 |
| Popis: | This paper proposes an enhanced Simultaneous Localization and Mapping (SLAM) algorithm based on matching laser image and Extended Kalman Filter (EKF). In general, laser information is one of the most efficient data for localization of mobile robots and is more accurate than encoder data. For localization of a mobile robot, moving distance information of a robot is often obtained by encoders and distance information from the robot to landmarks is estimated by various sensors. Though encoder has high resolution, it is difficult to estimate current position of a robot precisely because of encoder error caused by slip and backlash of wheels. In this paper, the position and angle of the robot are estimated by comparing laser images obtained from laser scanner with high accuracy. In addition, Speeded Up Robust Features (SURF) is used for extracting feature points at previous laser image and current laser image by comparing feature points. As a result, the moving distance and heading angle are obtained based on information of available points. The experimental results using the proposed laser slam algorithm show effectiveness for the SLAM of robot. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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