You're invited to attend
"Autonomous Navigation, Mapping, and Exploration"
Assistant Professor | Department of Intelligent Systems Engineering
Monday, March 27
2 - 3 p.m.
Weber Lecture Hall 2
About the Seminar:
In this talk, I will present our recent achievements on autonomous robotic systems including unmanned ground, aerial and aquatic vehicles. I will first discuss a new framework that can simultaneously accomplish multiple objectives that are essential to robot autonomy including identifying free space for navigation, building a topological representation for mapping, and ensuring good spatial coverage for unknown space exploration such as exploring wild forests. Different from existing work that model these critical objectives separately, I will show that navigation, mapping, and exploration can be derived with the same foundation modeled with a sparse variant of Gaussian Process. Then I will discuss a data-driven adaptive sensing framework that can be used for fast mapping/modeling unknown environments such as vast ocean floors and characterizing spatiotemporal distribution of air/water pollution. We consider real-world constraints such as multiple mission objectives and underlying model non-stationarity, and preliminary results from an unmanned surface vehicle also demonstrate high efficiency of our solution. Finally, I would like to discuss our recent progress on the stochastic motion planning and control for autonomous maneuver in cluttered and complex environments under disturbances. Results from unmanned ground vehicles demonstrate the applicability in challenging real-world scenarios.
About the Speaker:
Lantao Liu is an Assistant Professor in the Department of Intelligent Systems Engineering at Indiana University-Bloomington. His main research interest lies in Autonomy that integrates real physical robotic systems with data driven methods. He has been working on various autonomous systems involving single or multiple robots, and his various unmanned vehicles (air, ground, aquatic) have been deployed to the real world with “field trials” in those complex and unstructured environments such as construction sites, emergency sites, farmlands, outdoor air/water, etc. He has received multiple best paper awards and nominations in important robotics venues such as Robotics Science and Systems (RSS), International Conference on Intelligent Robots and Systems (IROS) and International Symposium on Distributed Autonomous Robotic Systems (DARS). He also received CAREER award and Amazon Machine Learning Research Award. His research has been supported by NSF, ARO, NAVSEA, USACE, USDA, and Amazon. Before joining Indiana University, he was a Postdoctoral Research Associate in the Department of Computer Science at the University of Southern California during 2015 - 2017. He also worked as a Postdoctoral Fellow in the Field Robotics Center of Robotics Institute at Carnegie Mellon University during 2013 - 2015. He received a Ph.D. from the Department of Computer Science and Engineering at Texas A&M University in 2013.