Optimal Motion Estimation from Visual and Inertial Measurements

Dennis Strelow and Sanjiv Singh
Proceedings of the Workshop on Integration of Vision and Inertial Sensors (INERVIS 2003), June, 2003.


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Abstract
We present two algorithms for estimating sensor motion from image and inertial measurements, which are suitable for use with inexpensive inertial sensors and in environments without known fiducials. The first algorithm is a batch method, which produces optimal estimates of the sensor motion, scene structure, and other parameters using measurements from the entire observation sequence simultaneously. The second algorithm recovers sensor motion, scene structure, and other parameters in an online manner, is suitable for use with long or "infinite" sequences, and handles sequences in which no feature is always visible. We also describe initial results from running each algorithm on a sequence for which ground truth is available. We show that while image measurements alone are not sufficient for accurate motion estimation from this sequence, both batch and online estimation from image and inertial measurements produce accurate estimates of the sensors' motion.

Notes
Associated Center(s) / Consortia: Field Robotics Center
Number of pages: 8

Text Reference
Dennis Strelow and Sanjiv Singh, "Optimal Motion Estimation from Visual and Inertial Measurements," Proceedings of the Workshop on Integration of Vision and Inertial Sensors (INERVIS 2003), June, 2003.

BibTeX Reference
@inproceedings{Strelow_2003_4916,
   author = "Dennis Strelow and Sanjiv Singh",
   title = "Optimal Motion Estimation from Visual and Inertial Measurements",
   booktitle = "Proceedings of the Workshop on Integration of Vision and Inertial Sensors (INERVIS 2003)",
   month = "June",
   year = "2003",
}