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Simultaneous Localization and Mapping in a Hybrid Robot and Camera Network System

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Abstract

To obtain accurate grid maps of large environments equipped with camera networks in real time, a two-level mapping method is presented in this paper. The local map level is composed of a set of local maps. Once a mobile robot enters a new camera visual field, a new local map corresponding to the camera is built by a Rao-Blackwellized particle filter (RBPF) method using the data from the robot’s laser sensor and odometry. During the local mapping process, a camera-calibration problem is also solved by using a marker attached to the robot which moves as a curve fashion in the camera visual field. The global level is an adjacency graph whose arcs are labeled with the relative transformations between local maps. Among these relative transformations, of particular important are the revisiting constraints. When the robot returns a previous local map, it can be detected and relocated by a calibrated camera corresponding to the local map. Then a revisiting constraint can be attained and added into global constraints. To have an accurate and consistent global map, a stochastic gradient descent (SGD) algorithm based on a simple state space is employed to optimize the existed graph after adding and updating each global constraint. Experimental results carried out with a real mobile robot in a large-scale indoor environment illustrate the advantages of our methods over two current state-of-the-art approaches.

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References

  1. Smith, R., Self, M.P., Cheeseman, P.: Estimating uncertain spatial relationships in robotics. Auton. Robot. Veh. 8, 167–193 (1990)

    Article  Google Scholar 

  2. Thrun, S., Burgard, W., Fox, D.: Probabilistic robotics. MIT press (2005)

  3. Lu, F., Milios, E.: Globally consistent range scan alignment for environment mapping. Auton. Robots 4, 333–349 (1997)

    Article  Google Scholar 

  4. Lu, F., Milios, E.: Robot pose estimation in unknown environments by matching 2D range scans. J. Intell. Robot. Syst. 18, 249–275 (1998)

    Article  Google Scholar 

  5. Javier, M., Florent, L., Luis, M.: Metric-based scan matching algorithm for mobile robot displacement estimation. In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 3557–3563, Barcelona, Spain (2005)

  6. Montemerlo, M., Thrun, S.: Simultaneous localization and mapping with unknown data association using FastSLAM. In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 1985–1991. Taipei, Taiwan (2003)

  7. Montemerlo, M., Thrun, S., Koller, D., Wegbreit, B.: FastSLAM: a factored solution to the simultaneous localization and mapping problem. In: Proc. of the AAAI National Conference on Artificial Intelligence, pp. 583–598 (2002)

  8. Doucet, A., de Freitas, N., Murphy, K., Russell, S.: Rao-Balckwellised particle filtering for dynamic Bayesian networks. In: Proc. of Sixteenth Conference on Uncertainty in Artificial Intelligence, pp. 176–183 (2000)

  9. Hahnel, D., Burgard, W., Fox, D., Thrun, S.: An efficient FastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements. In: Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems (IROS), pp. 27–31. Las Vegas, USA (2003)

  10. Grisetti, G., Tipaldi, G., Stachniss, C., Burgard, W., Nardi, D.: Fast and accurate slam with Rao-Blackwellized particle filters. Robot. Auton. Syst. 55(1), 30–38 (2007)

    Article  Google Scholar 

  11. Grisetti, G., Stachniss, C., Burgard, W.: Improving Grid-Based SLAM with Rao-Blackwellized particle filters by adaptive proposals and selective resampling. In: Proc. of the Int. Conf. on Robotics and Automation (ICRA), pp. 2432–2437. Barcelona, Spain (2005)

  12. Eliazar, A., Parr, R.: DP-SLAM: Fast, robust simultaneous localization and mapping without predetermined landmarks. In: Proc. of the Int. Conf. on Artificial Intelligence (IJCAI) (2003)

  13. Elfes, A.: Sonar-based real-world mapping and navigation. IEEE Trans. Robot. Autom. 3(3), 249–265 (1987)

    Article  Google Scholar 

  14. Blanco, J.L., González, J., Fernández-Madrigal, J.A.: Subjective local maps for hybrid metric-topological SLAM. Robot. Auton. Syst. 57(1), 64–74 (2009)

    Article  Google Scholar 

  15. Blanco, J.L., Fernández-Madrigal, J.A., González, J.: Towards a unified Bayesian approach to hybrid metric-topological SLAM. IEEE Trans. Robot. 24(2), 259–270 (2008)

    Article  Google Scholar 

  16. Rekleitis, I., Meger, D., Dudek, G.: Simultaneous planning,localization, and mapping in a camera sensor network. Robot. Auton. Syst. 54, 921–932 (2006)

    Article  Google Scholar 

  17. Sogo, T., Kimoto, K., Ishiguro, H., Ishida, T.: Mobile robot navigation by a distributed vision system. J. Japan Robot. Soc. 17, 1009–1016 (1999)

    Article  Google Scholar 

  18. Morioka, K., Lee, J.H., Hashimoto, H.: Human centered robotics in intelligent space. In: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 2010–2015 (2002)

  19. Matsumoto, K., Chen, H.Y., Ota, J., Arai, T.: Automatic parameter identification for cooperative modular robots. In: Proc. of the IEEE Int. Symposium on Assembly and Task Planning, pp. 282–287 (2002)

  20. Ho, K.L., Newman, P.: Detecting loop closure with scene sequences. Int. J. Comput. Vis. 74 (3), 261–286 (2007)

    Article  Google Scholar 

  21. Carnegie Mellon Robot Navigation Toolkit (Carmen). Available at http://carmen.sourceforge.net (2008)

  22. Roy, N., Montemerlo, M., Thrun, S.: Perspectives on standardization in mobile robot programming. In: Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), pp. 2436–2441. Las Vegas, NV, USA (2003)

  23. Tsai, R.Y.: An efficient and accurate camera calibration technique for 3D machine vision. In: Proc of the IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 364–374. Miami Beach, FL (1986)

  24. Liang, Z., Ma, X., Dai, X.: Information-theoretic approaches based on sequential Monte Carlo to collaborative distributed sensors for mobile robot localization. J. Intell. Robot Syst. 52(2), 157–174 (2008)

    Article  Google Scholar 

  25. Robbins, H., Monro, S.: A stochastic approximation method. Ann. Math. Stat. 22, 400–407 (1951)

    Article  MathSciNet  Google Scholar 

  26. Strang, G.: Introduction to linear algebra. Wellesley-Cambridge Press (1993)

  27. Darken, C., Chang, J., Moody, J.: Learning rate schedules for faster stochastic gradient search. In: Proc. Neural Networks for Signal Processing 2, IEEE Press (1992)

  28. Simmons, R.: The inter-process communication (IPC) system http://www-2.cs.cmu.edu/afs/cs/project/TCA/www/ipc/ipc.html (2005)

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Acknowledgments

This paper was supported by the Program of NJUPT (Grant No. NY209020 & NY209018) and the Natural Science Foundation of China (Grant No. 60805032). We sincerely acknowledge constructive comments from editors and reviewers.

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Authors and Affiliations

  1. College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China

    Zhiwei Liang & Songhao Zhu

  2. Key Lab of MCCSE, Ministry of Education, Southeast University, Nanjing, 210096, China

    Fang Fang & Xin Jin

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  1. Zhiwei Liang
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  2. Songhao Zhu
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  3. Fang Fang
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  4. Xin Jin
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Correspondence to Zhiwei Liang.

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Liang, Z., Zhu, S., Fang, F. et al. Simultaneous Localization and Mapping in a Hybrid Robot and Camera Network System. J Intell Robot Syst 100, 1493–1508 (2020). https://doi.org/10.1007/s10846-010-9446-3

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