Structure design and system implementation of supermarket shopping robot based on deep learning

Abstract

To enhance the operating efficiency of supermarkets, reduce their labour costs, and satisfy people's shopping experiences, we present the design and implementation of a supermarket shopping robot based on deep learning. Firstly, the robot adopts high-performance STM32F407 as its main control chip and is powered by 4 DC motors. It relies on 12 grey-scale sensors, gyroscopes and other devices for path planning. Through the infrared detection module, detect whether there are goods in the cargo window, and use the manipulator to accurately grasp and place the goods. Secondly, design a shopping cart to replace the manual cart to maintain the robot's control of the shopping cart during the shopping process. Finally, the AlexNet network is used as the feature extractor to realise the rapid identification of the target cargos. The experimental results show that under the simulation of the real supermarket environment, the designed robot runs flexibly, stably and reliably, and can well complete the purchase and supply of commodities, which is in line with the development trend of artificial intelligence.