IS = { zkontrolovano 22 Jan 2014 },
  UPDATE  = { 2014-01-20 },
  author =	 {Kubelka, Vladimir},
  supervisor =	 {Reinstein, Michal},
  title =	 {Data Fusion for a Mobile Exploratory Robot},
  school =	 {Center for Machine Perception, K13133 FEE Czech Technical
  address =	 {Prague, Czech Republic},
  year =	 {2013},
  month =	 {June},
  day =		 {7},
  type =	 {{MSc Thesis CTU--CMP--2013--10}},
  issn =	 {1213-2365},
  pages =	 {106},
  figures =	 {55},
  authorship =	 {100},
  psurl =	 {[Kubelka-TR-2013-10.pdf]},
  project =	 {FP7-ICT-247870 NIFTi},
  annote =	 {A robust localization subsystem is a vital part of a mobile
                  robot system; many high-level functionalities depend on it
                  (mapping, autonomous navigation, task planning, sensor data
                  postprocessing etc.) We propose a localization system for an
                  Urban Search&Rescue robot being developed as a part of the
                  European research project NIFTi. We are aiming for a higher
                  grade of accuracy, fusing several sensor modalities to
                  combine their strong points. This fusion is done by means of
                  an error state Extended Kalman Filter and by advanced
                  measurement preprocessing to ensure suppression of the drift
                  of the sensor modalities world coordinate frames. The
                  proposed algorithm has been extensively tested both by
                  indoor and outdoor experiments (over 4 kilometers traveled
                  by the robot in demanding 3D environments with a
                  high-precision reference). Finally, to discover the true
                  limits of the sensor modalities under realistic failure
                  conditions, several fail-case experiments have been
                  performed and analyzed. },
  keywords =	 {mobile robotics, localization, EKF, data fusion, urban search and rescue},