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Visual Odometry and Mapping for Indoor Environments Using RGB-D Cameras

  • Conference paper
  • First Online:
Robotics (SBR 2014 2014, ROBOCONTROL 2014, LARS 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 507))

Abstract

RGB-D cameras (e.g. Microsoft Kinect) offer several sensing capabilities that can be suitable for Computer Vision and Robotics. Low cost, ease of deployment and video rate appearance and depth streams are examples of the most appealing features found on this class of devices. One major application that directly benefits from these sensors is Visual Odometry, a class of algorithms responsible to estimate the position and orientation of a moving agent at the same time that a map representation of the sensed environment is built. Aiming to compute 6DOF camera poses for robots in a fast and efficient way, a Visual Odometry system for RGB-D sensors is designed and proposed that allows real-time position estimation despite the fact that no specialized hardware such as modern GPUs is employed. Through a set of experiments carried out on publicly available benchmark and datasets, we show that the proposed system achieves localization accuracy and computational performance superior to the state-of-the-art RGB-D SLAM algorithm. Results are presented for a thorough evaluation of the algorithm, which involves processing over 6, 5 GB of data corresponding to more than 9000 RGB-D frames.

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Notes

  1. 1.

    https://svncvpr.in.tum.de/cvpr-ros-pkg/trunk/rgbd_benchmark/rgbd_benchmark_tools/data/rgbdslam/.

  2. 2.

    https://www.youtube.com/user/brunomfs/videos.

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Acknowledgments

This work is supported by the Coordination for the Improvement of Higher Education Personnel (CAPES) and the Funding Agency for Studies and Projects (FINEP).

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Authors and Affiliations

  1. Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte Natal, Natal, Brazil

    Bruno M. F. Silva & Luiz M. G. Gonçalves

Authors
  1. Bruno M. F. Silva
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  2. Luiz M. G. Gonçalves
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Corresponding author

Correspondence to Bruno M. F. Silva .

Editor information

Editors and Affiliations

  1. Universidade de São Paulo, São Carlos, São Paulo, Brazil

    Fernando S. Osório

  2. Universidade de São Paulo, São Carlos, São Paulo, Brazil

    Denis Fernando Wolf

  3. Universidade de São Paulo, São Carlos, São Paulo, Brazil

    Kalinka Castelo Branco

  4. Universidade de São Paulo, São Carlos, São Paulo, Brazil

    Valdir Grassi Jr.

  5. Universidade de São Paulo, São Carlos, São Paulo, Brazil

    Marcelo Becker

  6. Universidade de São Paulo, São Carlos, São Paulo, Brazil

    Roseli Romero

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Silva, B.M.F., Gonçalves, L.M.G. (2015). Visual Odometry and Mapping for Indoor Environments Using RGB-D Cameras. In: Osório, F., Wolf, D., Castelo Branco, K., Grassi Jr., V., Becker, M., Romero, R. (eds) Robotics. SBR 2014 ROBOCONTROL LARS 2014 2014 2014. Communications in Computer and Information Science, vol 507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48134-9_2

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  • DOI: https://doi.org/10.1007/978-3-662-48134-9_2

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