The Ubiquitous Computing Applications Laboratory (UbiCA Lab) and the company Keonn technologies work since 2013 in using robots and RFID to inventory retail stores. The scope of this research has been broadened along time to make it more general, more ambitious, and more challenging, given the fact that other groups at the Department have sound complementary expertise to target these challenges. An initial current focus is to explore the integration of the expertise at the Artificial Intelligence Group in algorithms for robot navigation and mapping

The overall objective is to develop systems using robots and/or drones equipped with RGB-D cameras, laser scanners, RFID readers, and all other sensors needed to capture all information that is necessary to recreate a digital replica of a retail store, including layout, fixtures, and products, on which to develop business use cases such as inventorying, planogram inspection, in-store picking, or customer assistance. To advance towards the above objective, we need to face several unsolved research challenges, including:

• Unassisted exploration: ideally, the robots and/or drones should be able to start operating by themselves in a new store with no previous information and without the need of a map or any previous calibration.

• Cooperative exploration: several robots and/or drones should be able to work together, sharing the necessary information to explore the store.

• Robust exploration: new algorithms and new sensors (e.g. RFID), previously not used in robotics, should be explored to make the exploration task robust in all environments.

• Sensor fusion: RFID, RGB-D cameras, lasers, ultrasound, IMUs, RTLS, beacons, and other sensors should be used together to obtain the most accurate model of the store, including layouts and planograms, product location and orientation, pricing and publicity labels, or safety related information.

• Multimodal exploration: robots and drones should work together, the robots providing navigation assistance and a power source for the drones, which in turn extend the robot’s reach into more difficult areas.

To know more:

• Presentation of the project at the Data-driven Knowledge Extraction Workshop, June 2016 (Slides)

• Nur, K., Morenza-Cinos, M., Carreras, A., & Pous, R. (2015). Projection of RFID-Obtained Product Information on a Retail Stores Indoor Panoramas. Intelligent Systems, IEEE, 30(6), 30-37.