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Remote retail monitoring and stock assessment using mobile robots

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This paper describes a Virtual Reality (VR) based system for automating data collection and surveying in a retail store using mobile robots. The manpower cost for surveying and monitoring the shelves in retail stores are high, because of which these activities are not repeated frequently causing reduced customer satisfaction and loss of revenue. Further, the accuracy of data collected may be improved by avoiding human related factors. We use a mobile robot platform with on-board cameras to monitor the shelves either autonomously or through tele-operation. A remote operator can control the robot from a console which shows a 3D of view of the store as well as, capture real images and videos of the store. The robot is designed to facilitate automatic detection of Out-of-Stock (OOS) situations. It would be possible for a single operator to control multiple robots placed at different stores thus optimizing the available resources. As the deployment of the proposed system does not require modifying existing infrastructure of the store, the cost of the entire solution is cheaper with shorter return-on-investment (ROI) period. © 2014 IEEE.




Kumar, S., Sharma, G., Kejriwal, N., Jain, S., Kamra, M., Singh, B., & Chauhan, V. K. (2014). Remote retail monitoring and stock assessment using mobile robots. In IEEE Conference on Technologies for Practical Robot Applications, TePRA. IEEE Computer Society.

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