李雪松博士目前是無人駕駛汽車方面的高級工程師，主要從事無人駕駛汽車的感知算法研究；在進入工業界前，他於2020在澳大利亞的新南威爾士大學獲得博士學位，博士課題是智能機器人的物體檢測方法；其學士和碩士學位分別於2013年和2016在武漢理工大學完成。他的研究課題主要包含：物體檢測，SLAM，優化算法，深度學習，和機器人學。
Dr. Xuesong Li is currently an advanced engineer, working on autonomous driving. Before entering into industry, he was a Ph.D. student in Mechatronic Engineering in University of New South Wales (Sydney) in 2016, and obtained the PhD degree in October 2022. The PhD thesis is about object detection for intelligent robots. His bachelor and master degree from Wuhan University of Technology in 2013 and 2016.
His research interests include object detection, SLAM, optimization, deep learning, stochastic estimation, computer vision, robotics.
Abstract:
多傳感器融合是把多傳感器或多源的信息和數據進行綜合的融合處理，以得到更多關於觀測環境的信息，其目的是從不同的維度得到關於觀測環境的一致性解釋，更準確地得到環境信息，從而提高感知系統的感知範圍，感知準確性和可靠性。智能機器人通常會裝備多個傳感器，如何激光雷達，攝像頭和毫米多雷達。如何把多傳感器有效地融合在一起對於工業應用和學術研究都是很重要的課題。這次匯報主要就是探討在智能駕駛方面多傳感器融合的最新進展和挑戰。
Sensor fusion is the process of combining sensor data or data derived from disparate sources such that the resulting information has less uncertainty than would be possible when these sources were used individually, which can help to improve perception scope, accuracy and reliability. Autonomous robot, including self-driving cars, are usually equipped with multiple-sensors, such as LiDAR, camera and Radar. How to fuse multiple-sensors is an important topic for both industrial application and academic research. This presentation will introduce the latest progress and challenges in fusion of LiDAR and camera under the context of autonomous driving.
時間：3月2日19:25-20:25（周三） 國合樓329