Abstract
Simultaneous localization and mapping (SLAM) is becoming one of the most attractive research focuses of robot control and visual processing. In this paper, robot performs a SLAM mission in an unknown and structured indoor environment with the Microsoft XBOX Kinect obtaining visual and depth information. The line features of the object as mapping elements are extracted from visual images, and according to the extraction result, the distance between line features of the object and the robot can be obtained to portray the object edge onto the map in 2D, and the distance is provided by depth data from the Kinect. Meanwhile the robot motion model is created for the trajectory plan. A method using the extended Kalman filter (EKF) is applied to provide a pose estimate for the robot motion trajectory. The SLAM strategy is demonstrated in simulation and experimental environment.
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Tu, Y., Huang, Z., Zhang, X., Yu, W., Xu, Y., Chen, B. (2015). The Mobile Robot SLAM Based on Depth and Visual Sensing in Structured Environment. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_32
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DOI: https://doi.org/10.1007/978-3-319-16841-8_32
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16840-1
Online ISBN: 978-3-319-16841-8
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