From Geometry to Semantics: Toward Efficient Autonomous Navigation in the Wild

Abstract

This talk presents a unified perspective on the emerging concept of spatial intelligence for embodied autonomous systems. We discuss recent progress in integrating geometric perception, semantic understanding, domain adaptation, and traversability prediction into cohesive decision-making frameworks. The presentation highlights how domain shifts across environments and sensing conditions fundamentally challenge existing perception systems, motivating new approaches for uncertainty-aware and context-aware spatial reasoning. Through examples spanning off-road navigation, forest robotics, and real-world field deployment, the talk demonstrates how combining semantic and geometric reasoning can enable more trustworthy autonomous behavior.

Bio

Dr. Lantao Liu is a Professor and Founding Director of Robotics in the Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington. He directs research in autonomous robotics, robot learning, embodied AI, and field robotics applications for autonomous systems operating across air, ground, and marine environments. His work spans both single-robot and multi-robot systems, with applications in smart transportation, high-speed autonomous racing, remote sensing, infrastructure inspection, and search-and-rescue operations.

At Indiana University, Dr. Liu led the development of the university’s cross-school Robotics B.S. degree program, helping establish a multidisciplinary robotics education and research ecosystem spanning computer science, AI, and systems engineering. Prior to joining Indiana University, he was a Postdoctoral Research Associate at the University of Southern California (2015–2017) and a Postdoctoral Fellow at the Robotics Institute at Carnegie Mellon University (2013–2015). He received his Ph.D. in Computer Science and Engineering from Texas A&M University in 2013.