This paper presents a new terrain traversability mapping method integrated into the Robotic Technology Kernel (RTK) that produces ground slope traversability cost information from LiDAR height maps. These ground slope maps are robust to a variety of off-road scenarios including areas of sparse or dense vegetation. A few simple and computationally efficient heuristics are applied to the ground slope maps to produce cost data that can be directly consumed by existing path planners in RTK, improving the navigation performance in the presence of steep terrain.