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.