Abstract:
Visual-inertial fusion for state estimation and mapping has recently drawn increased attention. The sensing modalities offer compelling complementary characteristics, since inertial measurements provide strong short-term temporal correlations, while visual correspondences in images form spatial (relative pose) correlations. Furthermore, inertial MEMS sensors have become increasingly small, cheap, and accurate. Traditionally, the visual-inertial odometry problem has been rather addressed with filtering formulations; in this seminar, however, an approach using nonlinear optimization is presented — inspired by recent work of the computer vision community solving large reconstruction problems using optimization. The full batch VIO problem becomes untractable quite quickly; mobile robotics, however, needs to comply with real-time constraints. To this end, a framework using partial linearization of error terms along with marginalization (variable elimination) is suggested that allows for a bounded optimization window using the notion of keyframes without compromising the inherent sparsity of the problem. We will go through the necessary mathematical machinery and present a quantitative evaluation as well as qualitative results from on-board Unmanned Aerial Systems (UAS).
Bio:
Stefan Leutenegger has obtained his PhD from ETH Zurich (Autonomous Systems Lab, ASL) in 2014, where he has has worked on solar airplane design from concepts to realization and flight testing, as well as related algorithms for navigation close to the terrain. His activities covered a broad range from structural, electrical and software engineering to the development of highly efficient, robust, and accurate algorithms for multi-sensor state estimation and mapping.
As part of his PhD work, Stefan spent three months at the robotics company Willow Garage in Menlo Park, California, in 2012 under the supervision of Dr. Kurt Konolige and Dr. Vincent Rabaud. Besides his involvement in engineering and science activities, Stefan had the ASL-internal lead in the European FP7 Projects “ICARUS” and “SHERPA” since the proposal writing phase. He has furthermore been involved in BSc and MSc student project supervision as well as for teaching a part of ASL’s Master course on Unmanned Aerial Systems. In October 2014, Stefan started as a lecturer of robotics at Imperial College London, working in Andy Davison’s Dyson Robotics Laboratory.