This paper presents the integration of digital twin technology and autonomous robotics for the efficient cleaning and maintenance of photovoltaic (PV) solar panels. The proposed approach combines the virtual modeling of a robotic cleaning system with real-time control and simulation, enabling predictive maintenance and optimization of energy production. Using Siemens NX and TIA Portal for the development of the digital twin, along with PLC S7-1200/1500 programming and MODBUS TCP communication, the system replicates the physical robot’s behavior with high accuracy. Additionally, a compact and energy-efficient autonomous robot was designed to operate without water, using microfiber brushes and smart control logic. The robot’s architecture includes multiple motors for movement, sensor-based decision-making, and protective mechanisms for cable management and surface safety. The cleaning logic, structured in sequential networks, ensures optimal power recovery, precise trajectory control, and minimization of energy loss due to panel soiling. Simulation results show up to a 30% reduction in cleaning time and a 15% increase in power output after implementation. These outcomes highlight the potential of merging digital twin platforms with intelligent autonomous systems for sustainable solar energy operations. The joint development showcases a scalable, replicable solution for remote solar farms, enhancing operational efficiency, safety, and environmental impact mitigation.