Research on Button Localization Technology for Perspective-Robust Elevator Interaction in Service Robotics

This paper studies elevator button recognition and localization technology based on the YOLOv5 algorithm, aiming to solve the problem of autonomous riding of service robots in the elevator environment. Elevator button recognition and localization is one of the key technologies in the field of robotics. Traditional methods limit the mobility of robots due to the strict requirements of the shooting angle and image alignment. This paper improves the YOLOv5 model by constructing a comprehensive data set and adopting image standardization and initial feature classification methods to achieve lightweight and performance improvement of the model. The experimental results show that the improved YOLOv5 model is superior to other object recognition models in precision rate, recall rate, mAP, and other indicators, achieving a balance between efficiency and recognition performance, and providing effective technical support for the application of service robots in elevator scenarios.