Publication

Abstract : The growing demand for smart home systems that need less energy and resources has led to the development of an interactive autonomous cleaning robot, which uses power and water efficiently during floor cleaning. The proposed system uses obstacle and edge detection together with a hydraulic system that uses water, based on the type of floor. A Convolutional Neural Network (CNN) model is deployed using ESP32-CAM to identify the five different floor types: ceramic, marble, wood, terrazzo, and carpets, and control the water for mopping based on the floor type. Different path planning algorithms are considered and tested. Based on the test results, the optimum path planning method is selected. The experimental results show that the system operates reliably while it consumes less power and uses water more effectively than traditional robotic cleaning systems.