Advanced Optimization of PV Panel Cleaning Robot Based on Machine Learning Algorithms

Abstract-This study introduces a robotic system designed to maintain photovoltaic (PV) panel efficiency by removing dust and debris that reduce energy output.The robot uses sensors and actuators to clean panels and adjusts its actions based on real-time environmental data.Engineered for efficiency and energy conservation, it includes cleaning brushes and movement modules.Machine learning techniques-convolutional neural networks (CNNs) for detecting dust and reinforcement learning (RL) for optimizing movement pathsenhance the robot's adaptability.These algorithms enable it to balance dust removal effectiveness, energy use, and time efficiency, optimizing its cleaning strategy for sustainable PV panel maintenance.