In this paper, automated retail shelf monitoring, that includes tag verification and on-shelf availability checking, is proposed using a robot vision system. The mobile robot platform with camera vision extracts images of the products and tags on the shelves. The tags images are processed using computer vision tools such as YOLOv5 and EasyOCR to detect the tags and extract all information to be compared with a database for compliance. The extracted images of the products are used to reconstruct the entire shelving unit, the YOLOv5 is used for object detection, and the depth estimation MiDas model is used to build the depth map image of the shelving unit. This combined method, based on object detection and depth estimation, is used to check on-shelf availability of the products. Experimentation is conducted using a small shelving unit. It has been found that the proposed procedure can verify products, tags and availability and insure on time shelf monitoring by the robot vision system.