Graphic visualization and recognition system based on electroluminescent devices and robotic arm

With the acceleration of digitization and informatization, graphic visualization has already become an indispensable tool and medium in modern society. Electroluminescent devices (EL), which refer to certain materials that release photons through internal electron leaps when excited by an electric field, can construct low-cost and flexible multispectral image sensors. In this paper, we propose an alternating current EL device based on a pyramidal conical structure luminescent layer and design a luminescent display image recognition system in combination with a convolutional neural network. The system can recognize the shapes of objects made of different materials while effectively reducing the influence of environmental factors on recognition accuracy, thus achieving a more efficient and reliable image recognition function. Multi-spectral imaging technology provides rich spectral information for the robot, which can provide richer and more comprehensive environment perception capability to meet the needs of diverse dynamic application scenarios. With the significant advantages of EL technology-based image recognition devices, such as high brightness, high contrast, low power consumption, long life, flexibility, and multispectral imaging capability, robots can adapt to complex dynamic environments and achieve higher recognition accuracy and operational efficiency.