Time：09:30, March 11, 2024
Venue: Rm. 503, School of Electronics and Information Engineering
Topic: Multimodal information fusion perception and environmental understanding for autonomous driving
Currently, with the rapid development of electrification and intelligence in the automotive industry, research in the field continues to receive significant attention. Some intelligent driver-assistance functions have already been implemented and put into mass production. However, to achieve fully autonomous driving, vehicles still need more detailed and high-speed perception of their surrounding environment, in order to effectively plan travel paths based on actual road conditions. This lecture specifically introduces current research status, hotspots, and future trends in environmental understanding for autonomous driving. It will mainly discuss the latest developments and market demands in research directions such as real-time perception lightweight deep learning models based on 3D LiDAR point cloud, semantic segmentation, and unknown obstacle detection.
Organizer:
Office of Science and Technology Administration
Lecturer: Zhang Bin
In August 2011, Zhang obtained bachelor’s degree from Harbin Engineering University, and in March 2017, he got Ph.D. in Engineering from the University of Electro-Communications in Japan. From April 2017 to March 2018, he worked at Nissan Motor Co. Ltd. Since April 2018, he has been working at Faculty of Engineering at Kanagawa University as associate professor, and head of the Intelligent Machinery Research Lab in Department of Mechanical Engineering. Zhang has published more than 110 papers, including over 50 papers indexed in SCIE and EI. He received the Best Paper awards at international conferences such as EAI6GN2023, ICDSP2022, and ICSR206. Zhang is also a member of IEEE, IEICE, Japan Society of Electrical Engineers, the Robotics Society of Japan, and the Japan Society of Mechanical Engineers.
