You're invited to attend

"Semantic Perception for Field Robots in the Wild"

by

Lu Gan

Postdoctoral Scholar | Graduate Aerospace Laboratories
California Institute of Technology (GALCIT)

Monday, March 6
 2 - 3 p.m.
Weber Lecture Hall 2

About the Seminar: 
When humans perceive and navigate complex environments, we identify various places and objects, i.e., semantics, and infer their properties, physics, and relationships from semantics based on prior knowledge and experience. However, it is challenging to enable robots and autonomous systems to have such a high-level understanding of their surroundings, given only noisy sensor measurements and limited onboard computing resources, especially for lightweight unmanned aerial systems. In this talk, I will focus on the semantic perception system I developed for field robots that uses semantics as a pivot to achieve high-level scene understanding and reliable state estimation for planning and control. In addition to bringing human-relevant semantics to robot perception in a 3D continuous semantic map representation for task planning, the system also reasons robot-relevant properties of the environment to assist more sophisticated robot behavior planning. Effective learning methods to enable semantics acquisition in the wild will also be discussed. Future research aims to extend current semantic perception to dynamics-aware robot perception and increase the understanding of environmental dynamics for autonomous systems in the wild.

About the Speaker: 
Lu Gan is currently a Postdoctoral Scholar at the Graduate Aerospace Laboratories of the California Institute of Technology (GALCIT), affiliated with the Center of Autonomous Systems and Technologies (CAST). She received a B.S. degree in automation from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2013, and an M.S. degree in control engineering from the Beijing University of Aeronautics and Astronautics (BUAA), Beijing, China, in 2016. After that, she received her M.S. and Ph.D. in robotics from the University of Michigan, Ann Arbor, MI, USA, in 2021 and 2022. Her research interests revolve around perception and navigation for autonomous systems. She is currently an Associate Editor of IEEE Robotics & Automation Letters (RA-L), and an Associate Co-Chair of the IEEE Robotics & Automation Society (RAS) Technical Committee for Computer & Robot Vision. She was named a Rising Star in Data Science by the University of Chicago in 2022.