Abstract
The Simultaneous Localization and Mapping problem limits the promotion of home cleaning robots in practical domestic environments. In this paper, a novel topological-vector based simultaneous localization and mapping (TVSLAM) algorithm is proposed to solve the problem. The algorithm involves four aspects. First, the ultra-wideband localization and dead reckoning localization are selected to develop a new combined localization algorithm which can improve the localization accuracy. In addition, a data acquisition algorithm which simplifies the process of data collection and demands much smaller memory size is proposed. Furthermore, a partitioning algorithm is developed to adapt to the various change rates of different rooms. Finally, an autonomous learning algorithm based on the regular and repetitive cleaning task is put forward. It makes the constructed map approach to the real environment with the increase of cleaning times. Overall, a novel topological-vector map is generated according to the above process of the algorithm. Simulation results show that the TVSLAM is an efficient and robust localization and mapping algorithm.
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References
Lee, T.-K., Baek, S., Oh, S.-Y.: Sector-based maximal online coverage of unknown environments for cleaning robots with limited sensing. Robot. Autonom. Syst. 59(10), 698–710 (2011)
Sohn, H.J., Kim, B.K.: VecSLAM: an efficient vector-based SLAM algorithm for indoor environments. J. Intell. Rob. Syst. 56(3), 301–318 (2009)
Kang, J.-G., Kim, S., An, S.-Y., Oh, S.-Y.: A new approach to simultaneous localization and map building with implicit model learning using neuro evolutionary optimization. Appl. Intell. 36(1), 242–269 (2012)
Biswas, J., Veloso, M.: WiFi localization and navigation for autonomous indoor mobile robots. In: IEEE International Conference on Robotics and Automation, pp. 4379–4384 (2010)
Gutmann, J.S., Eade, E., Fong, P., Munich, M.E.: Vector field SLAM—Localization by learning the spatial variation of continuous signals. IEEE Trans. Rob. 28(3), 650–667 (2012)
Segura, M., Mut, V., Sisterna, C.: Ultra wideband indoor navigation system. Iet Radar Sonar Navig. 6(5), 402–411 (2012)
Cho, B.-S., Moon, W.-S., Seo, W.-J., Baek, K.-R.: A dead reckoning localization system for mobile robots using inertial sensors and wheel revolution encoding. J. Mech. Sci. Technol. 25(11), 2907–2917 (2011)
Mautz, R.: Indoor Positioning Technologies. Südwestdeutscher Verlag für Hochschulschriften (2012)
Jelinek, A.: Vector maps in mobile robotics. Acta Polytech. CTU Proc. 2(2), 22–28 (2015)
Gonzalez, E., Alvarez, O., Diaz, Y., Parra, C., Bustacara, C.: BSA: a complete coverage algorithm. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA), pp. 2040–2044 (2005)
Choi, Y.H., Lee, T.K., Baek, S.H., Oh, S.Y.: Online complete coverage path planning for mobile robots based on linked spiral paths using constrained inverse distance transform. In: The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5788–5793 (2009)
Lee, T.-K., Baek, S.-H., Choi, Y.-H., Oh, S.-Y.: Smooth coverage path planning and control of mobile robots based on high-resolution grid map representation. Robot. Autonom. Syst. 59(10), 801–812 (2011)
Pfister, S.T., Roumeliotis, S.I., Burdick, J.W.: Weighted line fitting algorithms for mobile robot map building and efficient data representation. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1304–1311 (2003)
An, S.-Y., Kang, J.-G., Lee, L.-K., Oh, S.-Y.: SLAM with salient line feature extraction in indoor environments. In: International Conference on Control Automation Robotics and Vision, pp. 410–416 (2010)
An, S.-Y., Kang, J.-G., Lee, L.-K., Oh, S.-Y.: Line segment-based indoor mapping with salient line feature extraction. Adv. Robot. 26(5–6), 437–460 (2012)
Lee, S., Lee, S., Baek, S.: Vision-based kidnap recovery with SLAM for home cleaning robots. J. Intell. Rob. Syst. 67(1), 7–24 (2011)
Jung, J., Lee, S.M., Myung, H.: Indoor mobile robot localization and mapping based on ambient magnetic fields and aiding radio sources. IEEE Trans. Instrum. Meas. 64(7), 1922–1934 (2015)
Lee, S.M., Jung, J., Kim, S., Kim, I.J., Myung, H.: DV-SLAM (Dual-sensor-based Vector-field SLAM) and observability analysis. IEEE Trans. Industr. Electron. 62(2), 1101–1112 (2015)
Choi, Y.-H., Lee, T.-K., Oh, S.-Y.: A line feature based SLAM with low grade range sensors using geometric constraints and active exploration for mobile robot. Autonom. Robots 24(1), 13–27 (2008)
Baizid, K., Lozenguez, G., Fabresse, L., Bouraqadi, N.: Vector maps: a lightweight and accurate map format for multi-robot systems. In: Kubota, N., Kiguchi, K., Liu, H., Obo, T. (eds.) ICIRA 2016. LNCS, vol. 9834, pp. 418–429. Springer, Cham (2016). doi:10.1007/978-3-319-43506-0_37
Sohn, H.J., Kim, B.K.: An efficient localization algorithm based on vector matching for mobile robots using laser range finders. J. Intell. Rob. Syst. 51(4), 461–488 (2008)
Thrun, S.: Learning metric-topological maps for indoor mobile robot navigation. Artif. Intell. 99(1), 21–71 (1998)
Abrate, F., Bona, B., Indri, M.: Experimental EKF-based SLAM for Mini-rovers with IR Sensors Only. In: EMCR (2007)
Dugarjav, B., Lee, S.-G., Kim, D., Kim, J.H., Chong, N.Y.: Scan matching online cell decomposition for coverage path planning in an unknown environment. Int. J. Precis. Eng. Manufact. 14(9), 1551–1558 (2013)
Baek, S., Lee, T.-K., Se-Young, O.H., Ju, K.: Integrated on-line localization, mapping and coverage algorithm of unknown environments for robotic vacuum cleaners based on minimal sensing. Adv. Robot. 25(13–14), 1651–1673 (2012)
Myung, H., Jeon, H.-M., Jeong, W.-Y.: Virtual door algorithm for coverage path planning of mobile robot. In: IEEE International Symposium on Industrial Electronics (ISIE), pp. 658–663 (2009)
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Chen, Y., Qu, C., Wang, Q., Jin, Z., Shen, M., Shen, J. (2017). TVSLAM: An Efficient Topological-Vector Based SLAM Algorithm for Home Cleaning Robots. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10464. Springer, Cham. https://doi.org/10.1007/978-3-319-65298-6_16
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