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Tactile sensing for ground classification

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EN
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EN
This paper describes the ground classification procedure for a six-legged walking robot. The terrain is classified according to the information gathered with the 6-DOF torque-force sensors. The statistical description of the obtained signals allow to obtain compact representation of the contact type for each 6-DOF component. Namely, the 4-element vector [variance, skewness, kurtosis, fifth moment] was used. Subsequently Discriminant Analysis was applied separately for classification of each component of the 6-DOF vector. The signal which gives the best classifica tion rate was established. The obtained result provides the information for the design of the new contact sensors for the robot feet.
Twórcy
autor
  • Poznań University of Technology, Institute of Control and Information Engineering, ul. Piotrowo 3A, 60-965 Poznań, Poland
Bibliografia
  • [1] C. M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics), Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2006.
  • [2] C. Brooks, K. Iagnemma, ,,Vibration-based terrain classification for planetary exploration rovers", IEEE Transactions on Robotics, 21(6):1185-1191, December 2005.
  • [3] P. Giguere, G. Dudek, ,,Clustering sensor data for autonomous terrain identification using timedependency", Auton. Robots, 26(2-3):171-186, April 2009.
  • [4] P. Giguere, G. Dudek, ,,Surface identification using simple contact dynamics for mobile robots", In: IEEE International Conference on Robotics and Automation (ICRA '09), pp. 3301-3306, May 2009.
  • [5] P. Giguere, G. Dudek, ,,A Simple Tactile Probe for Surface Identification by Mobile Robots", IEEE Transactions on Robotics, 27(3):534-544, June 2011.
  • [6] P. Giguère, G. Dudek, S. Saunderson, C. Prahacs, ,,Environment Identification for a Running Robot Using Inertial and Actuator Cues", In: G. S. Sukhatme, S. Schaal, W. Burgard, D. Fox (eds.), Robotics: Science and Systems, The MIT Press, 2006.
  • [7] M. Hoepflinger, C. Remy, M. Hutter, L. Spinello, R. Siegwart, ,,Haptic terrain classification for legged robots", In: IEEE International Conference on Robotics and Automation (ICRA), pp. 2828-2833, May 2010.
  • [8] R. Hoffman, E. Krotkov, ,,Perception of rugged terrain for a walking robot: true confessions and new directions", In: IEEE/RSJ International Workshop on Intelligent Robots and Systems (IROS '91), pp. 1505-1510, vol. 3, November 1991.
  • [9] E. Krotkov, ,,Active perception of material and shape by a walking robot", In: Fifth International Conference on Advanced Robotics ('91 ICAR). 'Robots in Unstructured Environments', pp. 37-42, vol. 1, June 1991.
  • [10] M. MacLellan, A. Patla, ,,Adaptations of walking pattern on a compliant surface to regulate dynamic stability", Experimental Brain Research, 173:521-530, 2006.
  • [11] M. MacLellan, A. Patla, ,,Stepping over an obstacle on a compliant travel surface reveals adaptive and maladaptive changes in locomotion patterns", Experimental Brain Research, 173:554-554, 2006.
  • [12] L. Ojeda, J. Borenstein, G. Witus, and R. Karlsen, ,,Terrain characterization and classification with a mobile robot", Journal of Field Robotics,23(2):103-122, 2006.
  • [13] K. Walas, D. Belter, ,,Messor - versatile walking robot for search and rescue missions", Journal of Automation, Mobile Robotics & Intelligent Systems,5(2):28-34, 2011.
  • [14] C. Weiss, H. Frohlich, A. Zell, ,,Vibration-based Terrain Classification Using Support Vector Machines", In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4429-4434, October 2006.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-f24a68c4-db73-4fd4-b9fb-0777cd0c3dbc
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