Humanoid odometric localization integrating kinematic, inertial and visual information

@article{Oriolo2016HumanoidOL,
  title={Humanoid odometric localization integrating kinematic, inertial and visual information},
  author={Giuseppe Oriolo and Antonio Paolillo and Lorenzo Rosa and Marilena Vendittelli},
  journal={Auton. Robots},
  year={2016},
  volume={40},
  pages={867-879}
}
We present a method for odometric localization of humanoid robots using standard sensing equipment, i.e., a monocular camera, an inertial measurement unit (IMU), joint encoders and foot pressure sensors. Data from all these sources are integrated using the prediction-correction paradigm of the Extended Kalman Filter. Position and orientation of the torso, defined as the representative body of the robot, are predicted through kinematic computations based on joint encoder readings; an… CONTINUE READING