Consistent ground-plane mapping: A case study utilizing low-cost sensor measurements and a satellite image

Vision-aided localization systems are often utilized in urban settings to take advantage of structured environment, high availability of unique visual features, as well as complimenting aiding measurements from Global Navigation Satellite System (GNSS). In this paper, we present a case study for roadway texture mapping that combines low-cost sensor measurements that are already available on many production vehicles (e.g. single frequency GPS, wheel odometry, and a forward looking camera) together with a satellite image. The aim of the method presented here is to obtain high resolution texture of the ground plane that is consistent with the low-resolution satellite image through an optimization process that estimates the smooth vehicle trajectory using Maximum-a-Posteriori (MAP). The main benefit of this system comes from the facts that: (1) it utilizes only low-cost sensors and information that are readily available, (2) it can be easily embedded into existing maps. Data and analysis of a drive captured around a block is used in this study.