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Development of an inspection system for waterway tunnels based on visual SLAM by an autonomous water robot

In recent years, due to the shortage of labor caused by an aging population and low birth rate in Japan, various research on robots has been conducted. There are many industries in which applying autonomous mobile robots are important, for instance, the inspection system for waterway tunnels. Entering the waterway tunnel is a difficult task for humans, thus, the dark and damp environment of a waterway tunnel is unfriendly to humans both in the physical way and mental ways. To solve that problem, various vSLAM methods have been proposed in the past, including feature-based methods, direct methods, and RGB-D methods. However, bad illuminance condition and unclear texture of the ceiling and walls of a waterway tunnel brings difficulties to many vSLAM algorithms and frameworks. To improve the accuracy of vSLAM, various methods have been proposed, such as sensor fusion. In this paper, we proposed a system that contains an online tracking using Intel REALSENSE T265 and an offline map reconstruction based on opengl using the data gathered by Intel REALSENSE T265. For the experiments, we conducted two comparison experiments based on openvslam framework and our proposed system. The results show that our proposed system can successfully track the camera positions and construct a map.