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Mobile Robot SLAM Interacting with Networked Small Intelligent Sensors Distributed in Indoor Environments

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Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7628))

Abstract

SLAM is a method of map building and self-position estimation for robot navigation. However, map building error is especially appeared in loop closing points when the mobile robot moves around loop trajectories. In this study, more accurate mobile robot SLAM is considered in intelligent space [1] where many sensors are distributed.

An intelligent space is constructed with various types of distributed sensors including networked laser range sensors. Laser sensor on a mobile robot and environment sensors share sensor information each other in intelligent space. Maps and self-positions of the mobile robot are estimated using geometrical relationships between the mobile robot and sensors in intelligent space. However, geometrical calibration of distributed sensors under the unified world coordinates is required for construction of the intelligent space. When many sensors are distributed in wide area, it generally becomes complicated tasks to calibrate all sensors. In order to solve these problems, we consider extend SLAM algorithm. In this study, a new method of SLAM, which uses distributed sensors fixed in the intelligent space, is introduced. This method aims to achieve precision SLAM and position estimation of networked laser range sensors in the intelligent space.

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References

  1. Lee, J.-H., Hashimoto, H.: Intelligent Space - concept and contents. Advanced Robotics 16(3), 265–280 (2002)

    Article  Google Scholar 

  2. Thrun, S., et al.: Probabilistic Robotics, pp. 1–483. MIT Press (2007)

    Google Scholar 

  3. Morioka, K., et al.: Human-following mobile robot in a distributed intelligent sensor network. IEEE Trans. on Industrial Electronics 51(1), 229–237 (2004)

    Article  Google Scholar 

  4. Kuroiwa, S., Morioka, K.: Development of Easy Camera Calibration Tool under Unified World Coordinate System Using Online Three-dimensional Reconstruction. In: Proc. of the 17th International Symposium on Artificial Life and Robotics, pp. 1179–1182 (2012)

    Google Scholar 

  5. Haehnel, D., et al.: A highly efficient FastSLAM algorithm for generating cyclic maps of large-scale environments from raw laser range measurements. In: Proc. of IROS, pp. 1–6 (2003)

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  6. Stachniss, C., Hähnel, D., Burgard, W.: Exploration with Active Loop-Closing for FastSLAM, pp. 1–6 (2004)

    Google Scholar 

  7. Lu, F., Milios, E.: Robot Pose Estimation in Unknown Environments by matching 2D Range Scans. Journal of Intelligent and Robotic Systems 18, 249–275 (1997)

    Article  Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Hashikawa, F., Morioka, K., Ando, N. (2012). Mobile Robot SLAM Interacting with Networked Small Intelligent Sensors Distributed in Indoor Environments. In: Noda, I., Ando, N., Brugali, D., Kuffner, J.J. (eds) Simulation, Modeling, and Programming for Autonomous Robots. SIMPAR 2012. Lecture Notes in Computer Science(), vol 7628. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34327-8_26

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  • DOI: https://doi.org/10.1007/978-3-642-34327-8_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34326-1

  • Online ISBN: 978-3-642-34327-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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