RFly Drone

Could This Warehouse Drone Cut Inventory Costs?

MIT's RFly enables small, safe, aerial drones to read RFID tags from tens of meters away while identifying the tags’ locations with an average error of about 19 centimeters.

Supply chain executives are always looking to find new ways to take inventory that are faster, cheaper and more efficient.

Mismatches between inventory records and actual stock exact a high cost in the retail industry. For example, Walmart reported in 2013, that it lost $3 billion in revenue due to that mismatch.

Well MIT researchers have a solution. They developed a system, called RFly, that enables small, safe, aerial drones to read RFID tags from tens of meters away while identifying the tags’ locations with an average error of about 19 centimeters.

In an article on MIT news, Larry Hardesty explained how the system works.

The central challenge in designing the system was that, with the current state of autonomous navigation, the only drones safe enough to fly within close range of humans are small, lightweight drones with plastic rotors, which wouldn’t cause injuries in the event of a collision. But those drones are too small to carry RFID readers with a range of more than a few centimeters.

The researchers met this challenge by using the drones to relay signals emitted by a standard RFID reader. This not only solves the safety problem but also means that drones could be deployed in conjunction with existing RFID inventory systems, without the need for new tags, readers, or reader software.

The drone would be especially useful in large warehouses for continuous monitoring, to prevent inventory mismatches, and to locate individual items quickly.

In developing the drone, researchers had to address some issues involved with relaying RFID signals and using them to determine tags’ locations. So the MIT researchers also equip each of their drones with its own RFID tag. A drone alternates between relaying the reader’s signal to a tagged item and simply letting its own tag reflect the signal back, so that the reader can estimate the drone’s contribution to the total phase shift and remove it.

In experiments in the Media Lab that involved tagged objects, many of which were intentionally hidden to approximate the condition of merchandise heaped in piles on warehouse shelves, the system was able to localize the tags with 19-centimeter accuracy while extending the range of the reader tenfold in all directions, or one hundredfold cumulatively. The researchers are currently conducting a second set of experiments in the warehouse of a major Massachusetts retailer.

 

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