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The U.S. Department of Energy Solar Energy Technologies Office (SETO) wants to improve access to solar energy through innovative technologies that will help to lower costs and expedite construction of utility-scale solar plants, or “solar farms.”
Lowering the levelized cost of solar energy is of paramount concern to the solar industry in order to make it a competitive form of energy relative to fossil fuel alternatives. The construction of a solar farm currently requires significant manual labor to set photovoltaic (PV) modules onto mounting hardware, which poses several challenges. Given the size and bulk of PV modules, this work is hazardous, physically taxing, and ergonomically challenging for laborers. The manual placement of PV modules on their frames requires consistent heavy lifting, which can lead to repetitive stress injuries. In addition, as workers become fatigued, mistakes are more likely to occur, such as the incorrect orientation of solar modules, which can significantly affect plant circuitry and limit its life. Modules are made of fragile componentry, such as glass, and can crack or break easily if mishandled. Given the nature of this work, as well as the competition for manual labor, labor costs are rising. As a result, the industry is experiencing labor shortages. SETO is looking for solutions providers to develop technology that will not only enhance labor productivity and safety, but also reduce construction costs and accelerate the construction of solar fields by automating solar module installation tasks.
RE2 received a $1.9 million award from SETO to develop a new, outdoor, autonomous robotic system using state-of-the-art computer vision and machine-learning techniques. Called Outdoor Autonomous Manipulation of Photovoltaic Panels (O-AMPP), the system aims to reduce the time it takes to construct a new solar field by almost 40 percent. RE2 will use its outdoor RE2 Sapien™ robotic arms to support the transfer, manipulation and placement of solar modules. In addition, RE2 will use its machine learning and artificial intelligence software, RE2 Detect™ and RE2 Intellect™, to ensure that the system is capable of autonomously manipulating and placing PV modules to safely and efficiently construct a solar field.