Scan Planning for RGB-D Mapping Based on Grid Map

Autonomously building 3D maps is important for robots in real-world applications. Even the state-of-the-art RGB-D mapping techniques rely on manually collected image data. It is confronted with a great challenge since: (1) the distance and viewing angle of the data provided by RGB-D cameras are too limited, (2) and indoor scenes are too large compared to the valid data range of RGB-D cameras. In this paper, we develop a novel method to generate the scan plans toward the problem using 2D grid maps as priori knowledge and taking into account the drawbacks of RGB-D cameras and the limitations of RGB-D mapping systems. Scan plans allow robots to scan indoor environments autonomously with relevant grid maps. An implementation of this method is applied on our real robot, and proven to be robust and effective in experiments.

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