题目：Sensing and State Estimation for Autonomous Indoor

时间：2014年12月12日（周五）上午10点

地点：工控老楼414会议室

Abstract: Micro aerial vehicles (MAVs) offer exceptional mobility and perceptual capabilities over ground platforms, making them particularly suitable for search-and-rescue, disaster response, and inspection missions in which the vehicle must be able to navigate through complex three dimensional environments. In such missions, MAVs must be fully autonomous in order to stabilize their fast dynamics and react to changes in environmental conditions. In particular, Sensing and state estimation is the foremost important component for achieving high level of autonomy.

This talk summarizes our recent advances in autonomous MAVs and will consist of three parts: (1) algorithms and systems design for autonomous flight in GPS-denied indoor environments with a quadrotor MAV equipped with a laser scanner, an IMU, and limited onboard computation; (2) a robust multi-sensor fusion methodology for MAVs equipped with sensors with complementary failure modalities to enable autonomous navigation in complex environments; and (3) monocular visual-inertial state estimation methodologies that enable high-speed flight, on-the-fly initialization, and failure recovery. Extensive experimental results will be presented throughout the talk.

Bio: Prof. Shaojie Shen received his B.Eng. degree in Electronic Engineering (Honors Research Option) from the Hong Kong University of Science and Technology in 2009. He received his M.S. in Robotics and Ph.D. in Electrical and Systems Engineering in 2011 and 2014, respectively, all from the University of Pennsylvania. He joined the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology in September 2014 as an Assistant Professor. His research interests are in the areas of robotics and unmanned aerial vehicles, with focus on state estimation, sensor fusion, computer vision, localization and mapping, and autonomous navigation in complex environments. He also has extensive experience in trajectory planning and nonlinear control of multirotor aircrafts.