@Article{Hoffmann-RAS2014,
  IS = { zkontrolovano 26 Oct 2014 },
  UPDATE  = { 2014-10-02 },
  author =     {Hoffmann, Mat{\v e}j and {\v S}t{\v e}p{\' a}nov{\' a} Karla and Rein{\v s}tein, Michal},
  language =   {English},
  title =      {The effect of motor action and different sensory modalities on terrain classification in a quadruped robot running with multiple gaits},
  year =       {2014},
  month =      {April},
  pages =      {1790-1798},
  journal =    {Robotics and Autonomous Systems },
  publisher =  {Elsevier},
  address =    {Amsterdam},
  issn =       {0921-8890},
  volume =     {62},
  number =     {12},
  authorship = {},
  annote =     {Abstract Discriminating or classifying different
                  terrains is an important ability for every
                  autonomous mobile robot. A variety of sensors,
                  preprocessing techniques, and algorithms in
                  different robots were applied. However, little
                  attention was paid to the way sensory data was
                  generated and to the contribution of different
                  sensory modalities. In this work, a quadruped robot
                  traversing different grounds using a variety of
                  gaits is used, equipped with a collection of
                  proprioceptive (encoders on active, and passive
                  compliant joints), inertial, and foot pressure
                  sensors. The effect of different gaits on
                  classification performance is assessed and it is
                  demonstrated that separate terrain classifiers for
                  each motor program should be employed. Furthermore,
                  poor performance of randomly generated motor
                  commands confirms the importance of coordinated
                  behavior on sensory information structuring. The
                  collection of sensors sensitive to active,
                  "tactile", terrain exploration proved
                  effective. Among the individual modalities, encoders
                  on passive compliant joints delivered best
                  results.},
  keywords =   {legged robots, terrain classification, active perception},
  project =    {SGS13/203/OHK3/3T/13, GACR 14-13876S},
  doi =        {http://dx.doi.org/10.1016/j.robot.2014.07.006},
  ut_isi =     {},
}