Abstract
The field of simultaneous localization and mapping (SLAM) has made tremendous progress in the last couple of decades, to the point where we have mature-enough methods and algorithms to explore applications on interesting scales both spatially and temporally. In this talk we discuss some of our current efforts in deploying large-scale, long-term SLAM systems in real-world field applications, and in particular, our current work in autonomous underwater ship hull inspection. We will discuss our developments in modeling the visual saliency of underwater imagery for pose-graph SLAM, how this saliency measure can be used within an active SLAM planning paradigm, and our development of generic linear constraints—a principled framework for pose-graph reduction, which is important for controlling multi-session SLAM graph complexity.