Abstract
We present a comparison of an extended Kalman filter and an adaptation of bundle adjustment from computer vision for mobile robot localization and mapping using a bearing-only sensor. We show results on synthetic and real examples and discuss some advantages and disadvantages of the techniques. The comparison leads to a novel combination of the two techniques which results in computational complexity near Kalman filters and performance near bundle adjustment on the examples shown.
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© 2001 Springer-Verlag Berlin Heidelberg
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Deans, M., Hebert, M. (2001). Experimental comparison of techniques for localization and mapping using a bearing-only sensor. In: Rus, D., Singh, S. (eds) Experimental Robotics VII. Lecture Notes in Control and Information Sciences, vol 271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45118-8_40
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DOI: https://doi.org/10.1007/3-540-45118-8_40
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