IS = { zkontrolovano 23 Jun 2013 },
  UPDATE  = { 2012-12-31 },
  author =     {Rein{\v s}tein, Michal and Hoffmann, Mat{\v e}j},
  language =   {English},
  title =      {Dead reckoning in a dynamic quadruped robot based on
                multimodal proprioceptive sensory information},
  c_title =    {Dead reckoning navigace pro dynamick{\' e}ho 
                {\v c}ty{\v r}noh{\' e}ho robota zalo{\v z}en{\' a} 
                na multimod{\' a}ln{\' \i} informaci z 
                proprioceptivn{\' \i}ch senzor{\accent23 u}},
  year =       {2013},
  month =      {April},
  pages =      {563-571},
  journal =    {IEEE Transactions on Robotics},
  publisher =  {IEEE Robotics and Automation Society},
  address =    {IEEE Publishing Operations, 445 Hoes Lane, Piscataway, NJ 08854},
  issn =       {1552-3098},
  volume =     {29},
  number =     {2},
  authorship = {70-30},
  annote =     {It is an important ability for any mobile robot to be
    able to estimate its posture and to gauge the distance it
    travelled. In this work, we have addressed this problem in a
    dynamic quadruped robot by combining traditional state estimation
    methods with machine learning. We have designed and implemented a
    navigation algorithm for full body state (position, velocity, and
    attitude) estimation that does not use any external reference, but
    relies on multimodal proprioceptive sensory information
    only. Extended Kalman Filter was used to provide error estimation
    and data fusion from two independent sources of information: (1)
    strapdown mechanization algorithm processing raw inertial data and
    (2) legged odometry. We have devised a novel legged odometer that
    combines information from a multimodal combination of sensors
    (joint and pressure). We have shown our method to work for a
    dynamic turning gait and we have also successfully demonstrated
    how it generalizes to different velocities and
    terrains. Furthermore, our solution proved to be immune to
    substantial slippage of the robot's feet. },
  keywords =   {legged robots, odometry, dead reckoning, 
    extended Kalman filter, path integration, slippage},
  project =    {FP7-ICT-247870 NIFTi},
  doi =        {10.1109/TRO.2012.2228309},
  ut_isi =     {000317493900020},