Study on an Improved Multi-Classifier Road Detection Applied to Navigation of Automatic Land Vehicle through Remote Calling

• Main Authors: Szu-Yu Shen, 沈思瑜
• Other Authors: Rong-Chin Lo
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/kh5h93

碩士 === 國立臺北科技大學 === 電腦與通訊研究所 === 99 === This research proposes a technique of calling an ALV remotely. Firstly, the calling side sends the GPS information of the target to the ALV through wireless network, then path planning is completed by prepared map data with Dijkstra algorithm. AdaBoost algorithm is introduced for implementing road detection; different types of classifiers are trained to detect different road surfaces. With the result of road detection, the ALV is able to find the drivable region eliminating the obstacles and not-road region. By determining the difference with the position of the ALV and current sub-goal on the planned path, the forward direction to the sub-goal is decided; with comparing it to the driving direction detect by digital compass, the direction of deflection can be decided. When ALV drives to the sub-goal, obstacles and not-road region is avoided by surpass. In conclusion, ALV can reach the calling side.