In this chapter, radar-based mapping of the environment for robotic applications or for automated driving is presented. The generation of a map of the environment is the basis for a wide range of applications in the field of robotics and autonomous systems, including the planning of driving trajectories, obstacle avoidance, or finding parking spaces. Grid maps have been known since the 1980s and provide a simple and effective method for storing, processing, merging and presenting information about the environment. The two-dimensional visualization of a grid map from a bird’s eye view allows an intuitive interpretation of the maps without in-depth technical knowledge. The efficient generation of grid maps makes them a fundamental basis for a wide range of applications. Grid maps segment a map into a uniform grid, either in two-dimensional or three-dimensional space, in order to create a corresponding image of the environment. In this chapter, amplitude grid maps (AGMs) as well as probabilistic occupancy grid maps (OGMs) are presented, and compared. Subsequently, the SLAM method is presented, which enables self-localization within the global map.