报告题目：A Tutorial on Extended Kalman Filter Approach to Implement Simultaneous Localization and Mapping
线上ZOOM会议 ID：966 4241 3868
With improvements in computer processing speed and availability of low cost sensors, such as cameras and laser range finders, simultaneous localization and mapping (SLAM) is now finding practical applications in autonomous navigation, robotics (e.g. home vacuum cleaners), virtual/ mixed reality. This talk will be an instructional step-by-step approach to carry out SLAM in 2 D with unknown point landmarks. The Extended Kalman Filter will be used to estimate both the robot’s pose and landmark locations in an unknown environment. If time permits, a MATLAB demonstration will also be shown. Anyone interested to work in Bayes filters, mobile robotics, estimation, will find this talk useful for practical implementation.
Dr. Jaspreet Dhupia is a Senior Lecturer in the University of Auckland in Mechatronics and Robotics developing novel automation, monitoring and control approaches to different application areas. Since obtaining his PhD from the University of Michigan, USA, in 2008 he had research career spanning USA, Singapore, China, Germany and New Zealand. He was an adjunct visiting professor to the Joint Institute at Shanghai Jiao Tong University in 2015 and 2016, and a visiting Fellow to Peking University in 2019. He is a Senior Member of IEEE and a Technical Editor of IEEE/ASME Transactions of Mechatronics and an Associate Editor for the ASME Dynamic Systems and Control Division.