this paper verifies a recently published method of
monocular depth computing in the context of visual SLAM. The
closed form depth solution was exploited in the measurement
model of a monocular EKF visual SLAM algorithm. SIFT
interest points are tracked during camera motion and a suitable
feature initialization is presented. The visual SLAM system is
verified through experiments on a mobile robot platform and the
results are benchmarked to ground truth.
Simultaneous localization and mapping, SLAM is an
important problem for several robotics applications [1]. Using
a camera as the main sensor, Visual SLAM, VSLAM has
attracted many researchers as a leading area of interest [2-4].
Depth calculation is necessary for this process and both mono
[5-6] and stereo [7-8] cameras have been used with VSLAM.
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