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S. Chroust, M. Vincze:
"Fusion of Vision and Inertia Data for Motion and Structure Estimation";
Journal of Robotics Systems, 21 (2004), 2; S. 73 - 83.

This paper presents a method to fuse measurements from a rigid sensor rig with a stereo
vision system and a set of 6 DOF inertial sensors for egomotion estimation and external
structure estimation. No assumptions about the sampling rate of the two sensors are
made. The basic idea is a common state vector and a common dynamic description which
is stored together with the time instant of the estimation. Every time one of the sensor
sends new data, the corresponding filter equation is updated and a new estimation is
generated. In this paper the filter equations for an extended Kalman filter are derived
together with considerations of the tuning. Simulations with real sensor data show the
successful implementation of this concept.

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