The Reflectance Field Map: Mapping Glass and Specular Surfaces in Dynamic Environments

We present the Reflectance Field Map, a reliable real-time method for detecting shiny surfaces, like glass, metal, and mirrors, with lidar. The Reflectance Field Map combines the theory developed for Light Field Mapping, common in computer graphics, with occupancy grid mapping. Like early methods for sonar-based robot mapping, we show how the addition of angular viewpoint information to a standard 2D grid map enables robust mapping in the presence of specular reflections. However unlike previous approaches, our method works in dynamic environments. Additionally, unlike recent approaches for lidar-based mapping of specular surfaces, our approach is sensor-agnostic and has no reliance on either intensity or multi-return measurements. We demonstrate the ability of the Reflectance Field Map to accurately map a campus environment containing numerous pedestrians and significant plate glass, both straight and curved. The algorithm runs in real-time (75+Hz) on a single core of a standard desktop processor. An open source implementation of the algorithm is available at https://github.com/collinej/reflectance_field_map.