Lidar and radar sensors are widely used to obtain depth information for various applications in the field of robotics, such as navigation [1] , collision avoidance [2] , surveillance [3] , and map generation [4] . These two sensors are becoming increasingly popular as perception systems for autonomous mobile robots. However, as a result of their versatility and popularity, lidar and radar sensors come in a variety of specifications, sizes, and prices. Consequently, it has become essential to quantitatively evaluate these two sensors from various situational perspectives. This is required for a comprehensive selection of the most appropriate sensors or combinations thereof for the target applications.
