Kinect v2 for mobile robot navigation: Evaluation and modeling

Abstract

With the introduction of the Microsoft Kinect for Windows v2 (Kinect v2), an exciting new sensor is available to robotics and computer vision researchers. Similar to the original Kinect, the sensor is capable of acquiring accurate depth images at high rates. This is useful for robot navigation as dense and robust maps of the environment can be created. Opposed to the original Kinect working with the structured light technology, the Kinect v2 is based on the time-of-flight measurement principle and might also be used outdoors in sunlight. In this paper, we evaluate the application of the Kinect v2 depth sensor for mobile robot navigation. The results of calibrating the intrinsic camera parameters are presented and the minimal range of the depth sensor is examined. We analyze the data quality of the measurements for indoors and outdoors in overcast and direct sunlight situations. To this end, we introduce empirically derived noise models for the Kinect v2 sensor in both axial and lateral directions. The noise models take the measurement distance, the angle of the observed surface, and the sunlight incidence angle into account. These models can be used in post-processing to filter the Kinect v2 depth images for a variety of applications.