Abstract
Both Laser scanner and Kinect has been widely used in robotic application for 2D Simultaneous Localization and Mapping (SLAM). The feasibility of sensors to build acquired maps are often due to the limited field of view of the sensors. In this work, we applied four methods of sensor patterns for SLAM: a single Kinect, two Kinects, a Laser scanner, a Kinect combine with a Laser scanner. For the two-sensor patterns, we proposed an efficient approach to merge the data from the both two sensors. Several SLAM algorithms (i.e. Gmapping, Hector and Crsm SLAM) were tested using the four methods to build accurate 2D maps. All the methods have been evaluated and compared in real world experiments with slight and complex features, then the performance of the three SLAM algorithms were compared particularly in the map accuracy by using the assessment algorithm of Local Grid Map Recursion Matching.
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References
Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT press, Cambridge (2005)
Quigley, M., et al.: ROS: an open-source robot operating system. In: IEEE International Conference on Robotics and Automation (ICRA), Workshop on Open Source Software (2009)
Leonard, J.J., Durrant-Whyte, H.F.: Directed Sonar Sensing for Mobile Robot Navigation, vol. 175. Springer, New York (1990)
Bruce, J., Veloso, M.M.: Real-time randomized path planning for robot navigation. In: Kaminka, G.A., Lima, P.U., Rojas, R. (eds.) RoboCup 2002. LNCS, vol. 2752, pp. 288–295. Springer, Heidelberg (2003). doi:10.1007/978-3-540-45135-8_23
Chávez, A., Karstoft, H.: Improvement of KinectTM sensor capabilities by fusion with laser sensing data using octree. Sensors 12(4), 3868–3878 (2012)
Kamarudin, K., Mamduh, S.M., Shakaff, A.Y.M., Saad, S.M., Zakaria, A., Abdullah, A.H., et aI.: Method to convert kinect’s 3D depth data to a 2D map for indoor SLAM. In: 9th IEEE Colloquium on Signal Processing and its Applications (CSPA 2013), Kuala Lumpur (2013)
Grisetti, G., Stachniss, C., Burgard, W.: Improved techniques for grid mapping with Rao-Blackwellized particle filters. Trans. Rob. 23(1), 34–46 (2007)
Kohlbrecher, S., Meyer, J., Von Stryk, O., Klingauf, U.: A Flexible and Scalable SLAM System with Full 3D Motion Estimation. In: The International Symposium on Safety, Security and Rescue Robotics (SSRR), November (2011)
Tsardoulias, E., Petrou, L.: Critical rays scan match SLAM. J. Intell. Rob. Syst. 72(3), 441–462 (2013)
Huang, S., Dissanayake, G.: Convergence and consistency analysis for extended Kalman filter based SLAM. IEEE Trans. Rob. 2(5), 1036–1049 (2007)
Wan, E.A., Merwe, R.V.D.: The unscented Kalman filter for nonlinear estimation. In: Adaptive Systems for Signal Processing, Communications, and Control Symposium, pp. 153–158. IEEE (2000)
Moravec, H.P., Elfes, A.: High resolution maps from angle sonar. In: ICRA 1985, pp. 116–121 (1985)
Srinivasan, K., Gu, J.: Multiple sensor fusion in mobile robot localization. In: Canadian Conference on Electrical & Computer Engineering, pp. 1207–1210 IEEE (2007)
Zug, S., Penzlin, F., Dietrich, A., et al.: Are laser scanners replaceable by Kinect sensors in robotic applications? In: IEEE International Symposium on Robotic and Sensors Environments, pp. 144–149. IEEE (2012)
Tuzel, O., Porikli, F., Meer, P.: Region covariance: a fast descriptor for detection and classification. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 589–600. Springer, Heidelberg (2006). doi:10.1007/11744047_45
Salvador, S., Chan, P.: Toward accurate dynamic time warping in linear time and space. Intell. Data Anal. 11(5), 561–580 (2007)
Santos, J.M., Portugal, D., Rocha, R.P.: An evaluation of 2D SLAM techniques available in Robot Operating System. In: IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 1–6 (2013)
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Lang, Q. et al. (2017). An Evaluation of 2D SLAM Techniques Based on Kinect and Laser Scanner. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2016. Communications in Computer and Information Science, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-5230-9_29
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DOI: https://doi.org/10.1007/978-981-10-5230-9_29
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