Date of Original Version

2000

Type

Conference Proceeding

Abstract or Description

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.

Included in

Robotics Commons

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Published In

Proceedings of the ISER '00 Seventh International Symposium on Experimental Robotics.