Abstract
3D map building can aid robots to accomplish high-level tasks. Using an inexpensive RGB-D camera, a 3D map can be built by estimating the camera pose using visual features. However, the mapping will easily fail if there lack a sufficient number of features. In this paper, a proactive 3D mapping framework is proposed using a mobile robot platform equipped with an RGB-D camera and a projector. Both the camera and the projector are mounted on pan-tilt units controlled by servo motors. With the motion of the camera pan-tilt unit and the movement of the robot, a binary hypothesis testing problem is modeled to evaluate the estimation accuracy of the camera pose. A pattern is generated by the projector to increase the number of features when the pose estimation has large errors based on the real-time evaluation. The experimental results show that the proposed approach improves the mapping performance in an indoor environment with sparse features.
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Du, J., Sheng, W., Cheng, Q., Liu, M. (2014). Proactive 3D Robot Mapping in Environments with Sparse Features. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8887. Springer, Cham. https://doi.org/10.1007/978-3-319-14249-4_74
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DOI: https://doi.org/10.1007/978-3-319-14249-4_74
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14248-7
Online ISBN: 978-3-319-14249-4
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