EVALUATION OF INTEL REALSENSE D455 CAMERA DEPTH ESTIMATION FOR INDOOR SLAM APPLICATIONS

Abstract

The aim of this study is to propose evaluation methodology for the quality assessment of depth cameras for indoor mapping applications. Specifically, we evaluate the RGBD sensor Intel Realsense D455 w.r.t. measurement accuracy and noise while investigating their dependence on two central parameters characterizing the measurement scenario simultaneously: measurement distance and inclination of observed surfaces. The evaluation results are presented two-dimensionally as a function of both parameters. To this aim, two evaluation studies are conducted. First, a checkerboard pattern is used as reference object in a controlled setting. Secondly, actual indoor mapping data resulting from the deployment of the evaluated sensor in the context of an RGBD-SLAM application is used to conduct a similar evaluation in representative conditions for the intended usage scenario of indoor mapping. In this case, a TLS scan of the respective indoor environment is used as reference for evaluation.