Modeling the World at Scale

Vision: reconstruct a model of the world that permits online level-of-detail extraction. The core idea in this project is to interactively integrate sensed 3D data of varying sources and scales into a topologically clean surface. Our varying-scale model then permits online extraction of seamless levels of detail for rendering with minimal aliasing and popping artifacts. For this, we develop new topological guarantees to minimize the needed geometry. By exploiting the inherent redundancy of 2D surfaces in 3D, we design a fast way to robustly detect changes that let users better control the scan acquisition process. The topologically clean output surface and the change detection permit easy processing of the geometry for common use cases such as autonomous navigation, environment learning, augmented reality displays of georeferenced semantic information. An example application is fusing and distributing scans from the built-in sensors of multiple autonomous vehicles (ground, air), for incidental map updating as well as guaranteed efficient collision detection and tracking changes for path planning.