Autonomous Floor Navigation Control of Mobile Robot Using Elevator Button Recognition with Deep Learning

This paper presents an autonomous floor navigation control system for a mobile robot that uses elevator button recognition with deep learning. The proposed system utilizes a deep neural network to recognize elevator buttons, enabling the mobile robot to operate elevators independently and navigate between floors. The system is trained on a large dataset of button images, allowing for accurate recognition of elevator buttons. Additionally, the mobile robot is equipped with sensors to detect and avoid obstacles, ensuring safe movement. The proposed system was tested in a real-world environment and demonstrated high accuracy and reliability in navigating between floors. The results show that the system can be used successfully to transport goods between floors in a timely and efficient manner, making it a promising solution for inter-floor transportation in multi-level buildings where autonomous floor navigation is required.