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Terrain map building for a walking robot equipped with an active 2D range sensor

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Języki publikacji
EN
Abstrakty
EN
This paper deals with problems of rough terrain perception and mapping for walking robots equipped with inexpensive optical range sensors providing 2D data only. Two different sensing modalities are considered: the structured light sensor, and the Hokuyo URG-04LX laser scanner. Measurement uncertainty in both sensors is taken into account, and different geometric configurations of these sensors on the walking robot are analysed, yielding the configurations that are best for the task of terrain perception. Then, application of the acquired range data in local terrain mapping is presented. The mapping algorithm as well as novel methods for removing map artifacts that result from qualitative errors in range measurements are detailed. Experimental results are provided.
Twórcy
autor
autor
  • Poznan University of Technology, Institute of Control and Information Engineering, ul. Piotrowo 3A, 60-965 Poznań, Poland, pl@cie.put.poznan.pl
Bibliografia
  • [1] M. D. Adams, Sensor modelling, design and data processing for autonomous navigation. Singapore, World Scientific 1999.
  • [2] D. Belter, P. Łabecki, P. Skrzypczynski, Map-based adaptive foothold planning for unstructured terrain walking. Proc. IEEE Int. Conf. on Robot. and Automat., Anchorage, 2010, pp. 5256–5261.
  • [3] D. Belter, K. Walas, Messor – versatile walking robot for search and rescue missions, Journal of Automation, Mobile Robotics and Intelligent Systems, 5(2), 2011, pp. 28–34.
  • [4] B. Gaßmann, L. Frommberger, R. Dillmann, K. Berns, Real-time 3D map building for local navigation of a walking robot in unstructured terrain, Proc. IEEE Int. Conf. on Intelligent Robots and Systems, Las Vegas, 2003, pp. 2185–2190.
  • [5] B. Gaßmann, J. M. Zöllner, R. Dillmann, Navigation of walking robots: localisation by odometry. Climbing and Walking Robots VIII, Berlin, Springer 2005, pp. 953–960.
  • [6] D. Ilstrup, G. H. Elkaim, Low Cost, low power structured light based obstacle detection, Proc. IEEE/ION Position, Location and Navigation Symp., Monterey, 2008, pp. 771–778.
  • [7] H. Kawata, A. Ohya, S. Yuta, W. Santosh, T. Mori, Development of ultra-small lightweight optical range sensor system, Proc. IEEE/RSJ Int. Conf. on Intell. Robots and Systems, Edmonton, 2005, pp. 1078–1083.
  • [8] L. Kneip, F. Tache, G. Caprari, R. Siegwart, Characterization of the compact Hokuyo URG-04LX 2D laser range scanner, Proc. IEEE Int. Conf. on Robotics and Automation, Kobe, 2009, pp. 1447–1454.
  • [9] J. Z. Kolter, Y. Kimz, A. Y. Ng, Stereo vision and terrain modeling for quadruped robots, Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Kobe, 2009, pp. 1557–1564.
  • [10] E. Krotkov, R. Hoffman, Terrain mapping for a walking planetary rover. IEEE Trans. Robot. and Automat., 10(6), 1994, pp. 728–739.
  • [11] V.-G. Loc, S. Roh, I.-M. Koo, D.-T. Tran, H.-M. Kim, H. Moon, H.-R. Choi, Sensing and gait planning of quadruped walking and climbing robot for traversing in complex environment, Robotics and Autonomous Systems, 58(5), 2010, pp. 666–675.
  • [12] P. Łabecki, A. Kasinski, An active vision system for a walking robot, Pomiary Automatyka Kontrola, 55(9), 2009, pp. 731–736 (in Polish).
  • [13] P. Łabecki, A. Łopatowski, P. Skrzypczynski, Terrain perception for a walking robot with a low-cost structured light sensor, Proc. European Conf. on Mobile Robots, Dubrovnik, 2009, pp. 199–204.
  • [14] P. Łabecki, Analysis and optimization of a structured light sensor configuration for terrain map building, Studies in Automation and Information Technology, 34, 2009, pp. 37–56 (in Polish).
  • [15] P. Łabecki, D. Rosinski, P. Skrzypczynski, Terrain perception and mapping in a walking robot with a compact 2D laser scanner, in: Emerging Trends in Mobile Robotics (H. Fujimoto et al., eds.), Singapore, World Scientific 2010, pp. 981–988.
  • [16] L. Matthies, T. Balch, B. Wilcox, Fast optical hazard detection for planetary rovers using multiple spot laser triangulation, Proc. IEEE Int. Conf. Robotics and Automation, 1997, Albuquerque, pp. 859–866.
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  • [18] Y. Okubo, C. Ye, J. Borenstein, Characterization of the Hokuyo URG-04LX laser rangefinder for mobile robot obstacle negotiation. Unmanned Systems Technology XI, Proc. SPIE 7332, 2009 (on-line).
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  • [20] J. Poppinga, A. Birk, K. Pathak, A Characterization of 3D sensors for response robots. RoboCup 2009: Robot Soccer World Cup XIII (red. J. Baltes et al.), LNAI Vol. 5949, Berlin, Springer 2010.
  • [21] A. Roennau, T. Kerscher, M. Ziegenmeyer, J. M. Zöllner, R. Dillmann, Six-legged walking in rough terrain based on foot point planning, in: Mobile Robotics: Solutions and Challenges (O. Tosun et al., eds.), Singapore, World Scientific, 2009, pp. 591–598.
  • [22] A. Schmidt, A. Kasinski, The visual SLAM system for a hexapod robot, in: Computer Vision and Graphics (L. Bolc et al., eds.), LNCS Vol. 6375, Berlin, Springer, 2010, pp. 260–267.
  • [23] P. Skrzypczynski, Perception uncertainty management in a mobile robot navigation system, Poznan, Wyd. Politechniki Poznanskiej 2007 (in Polish).
  • [24] P. Skrzypczynski, On qualitative uncertainty in range measurements from 2D laser scanners, Journal of Automation, Mobile Robotics and Intelligent Systems, 2(2), 2008, pp. 35–42.
  • [25] K.Walas, D. Belter, A. Kasinski, Control and environment sensing system for a six-legged robot, Journal of Automation, Mobile Robot. & Intell. Syst., 2(3), 2008, pp. 26–31.
  • [26] C. Ye, J. Borenstein, A novel filter for terrain mapping with laser rangefinders. IEEE Trans. Robot. And Automat., 20(5), 2004, pp. 913–921.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUJ8-0006-0017
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