Autonomous robotic systems that already pervade our daily lives face a host of challenging tasks, including stocktaking in a rapidly changing environment. To tackle this, a team at Skoltech’s Intelligent Space Robotics Lab in Moscow has proposed a novel method that helps build models depicting location-related demand dependencies and precise locations of lost and moved items.
The team, led by Professor Dzmitry Tsetserukou from Skoltech Space Centre, developed a robot capable of reading RFID tags with an accuracy of 0.3m. The robot monitors shoppers, notes the locations they find the most attractive and predicts demand. As a result, it gives useful tips to the retailer on where it is best to place an item in order to increase sales and profits.
“Existing solutions lack applicability to real-life situations in retailing, which may cause an unforeseeable loss of sales. Our solution provides the retailer with exhaustive information about demand distribution...