智能驾驶中的多传感器融合技术学术报告

发布者:周春宇发布时间:2022-03-01浏览次数:434



李雪松博士目前是无人驾驶汽车方面的高级工程师,主要从事无人驾驶汽车的感知算法研究;在进入工业界前,他于2020在澳大利亚的新南威尔士大学获得博士学位,博士课题是智能机器人的物体检测方法;其学士和硕士学位分别于2013年和2016在武汉理工大学完成。他的研究课题主要包含:物体检测,SLAM,优化算法,深度学习,和机器人学。


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:



多传感器融合是把多传感器或多源的信息和数据进行综合的融合处理,以得到更多关于观测环境的信息,其目的是从不同的维度得到关于观测环境的一致性解释,更准确地得到环境信息,从而提高感知系统的感知范围,感知准确性和可靠性。智能机器人通常会装备多个传感器,如何激光雷达,摄像头和毫米多雷达。如何把多传感器有效地融合在一起对于工业应用和学术研究都是很重要的课题。这次汇报主要就是探讨在智能驾驶方面多传感器融合的最新进展和挑战。


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.


时间:3219:25-20:25(周三) 国合楼329



返回原图
/