| Summary: | 碩士 === 國立臺北科技大學 === 電子工程系 === 107 === In recent years, object detection has been applied in many fields. In one of the most well-known fields, autonomous driving system, the key skill lies in the breakthrough of LiDAR (Light Detection and Ranging). As the core component of object detection, LiDAR can instantly gather a large amount of three-dimensional (3D) depth information with high accuracy, which allows users to rebuild three-dimensional environment. Through the information provided by LiDAR, autonomous driving system can identify all kinds of circumstances nearby and to choose a much safer route. The mainstream of applying LiDAR skill in autonomous system is the product of Velodyne, HDL-64. Based on HDL-64, this paper aims to decode the data packets which transform the information of original packet into the point cloud data of X, Y, Z. This will allow users to make use of decoding information in more research and applications such as rebuilding three-dimensional environment, making deeper object detection and object classification.
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