A Probabilistic Method Toward SLAM for Mobile Robotic Systems

  • R. S. Anoop
  • T. Gireeshkumar
  • G. Saisuriyaa
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 308)


Simultaneous localization and mapping (SLAM) problem helps a mobile robot in identifying its own position by providing an autonomously built map. This work proposes a software and hardware approach for online mobile robotic systems, which is capable of performing SLAM. The mapping of unknown environment with low-cost sensors, incorporating probabilistic method, is the highlight of this work. The hardware system comprises of a multisensor mobile robot developed on the ARM Cortex platform. The software part mainly incorporates pose graph data structure blended with mixture model, which is further optimized by stochastic gradient descent method


Simultaneous localization and mapping (SLAM) Probabilistic robotics Pose graph data structure Gaussian mixture model 


  1. 1.
    Frese, U.: A discussion of simultaneous localization and mapping. Auton. Robots 20(1), 25–42 (2006)CrossRefGoogle Scholar
  2. 2.
    Thrun, S., Burgard, W., Fox, D.: Probabilistic robotics. MIT press, Cambridge (2005)MATHGoogle Scholar
  3. 3.
    Pfingsthorn, M., Birk, A.: Simultaneous localization and mapping with multimodal probability distributions. Int. J. Robot. Res. 32(2), 143–171 (2013)CrossRefGoogle Scholar
  4. 4.
    Pfingsthorn, M., Birk, A.: Handling local and global ambiguities via a generalized graph SLAM framework based on multimodal and hyperedge constraints. ICRA Workshop on robust and multimodal inference in Factor Graphs (2013)Google Scholar
  5. 5.
    Reynolds, D.: Gaussian mixture models. Encycl. Biometrics, 659–663 (2009)Google Scholar
  6. 6.
    Fox, D., Burgard, W., Thrun, S.: Probabilistic methods for mobile robot mapping. In: Proceedings of the IJCAI-99 Workshop on Adaptive Spatial Representations of Dynamic Environments (1999)Google Scholar
  7. 7.
    Thrun, S., Burgard, W., Fox, D.: A probabilistic approach to concurrent mapping and localization for mobile robots. Auton. Robots 5(3–4), 253–271 (1998)CrossRefMATHGoogle Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Amrita Vishwa Vidyapeetham UniversityCoimbatoreIndia

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