Kinect V2 vs Intel RealSense D435: A Comparative Study on 3D Mapping

Abstract

The generation of accurate 3D maps is essential for an efficient autonomous navigation. With precise mapping, robots can plan optimal paths, avoiding obstacles and efficiently reaching their destinations. For this purpose, the use of RGB-D cameras, which capture color images and depth information of the environment, is common. This paper presents a comparative study of 3D maps generated by the Kinect V2 and RealSense D435 sensors, which were properly configured in a manipulator robot for controlled data acquisition, considering different environments and capture conditions. The RTAB-Map algorithm was used to process the data acquired by the sensors and generate the 3D maps. This analysis allows identifying which sensors are more suitable for each type of environment, as well as their limitations and advantages. Thus, this comparison helps select the best camera for each application and provides valuable insights for the development of more accurate and efficient applications.