The AI-powered computer vision of Maximo ensures precise panel placement. Credit: leolintang / Shutterstock.

American utility and power generation company AES Corporation has introduced Maximo, an AI-enabled solar installation robot.

The robot is designed to significantly improve the speed, efficiency and safety of solar panel installation.

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Maximo can install solar panels in half the time and at half the cost of traditional methods.

By collaborating with on-the-ground crews, the robot accelerates the deployment of renewable energy, consequently reducing the time-to-power for AES customers.

The AI-powered computer vision of Maximo ensures precise panel placement, crucial for enhancing installation accuracy.

Maximo features image reconstruction capability – a proprietary generative AI pipeline that can reconstruct images that are obscured by glare or other lighting conditions.

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The introduction of Maximo is not only expected to expedite project timelines but also to create new high-tech job opportunities and engage new segments of the workforce.

AES highlighted Maximo’s versatility, noting its effective performance in a range of climates and lighting conditions.

The system has also been validated through successful deployment across project sites in the US.

The utility company plans to deploy Maximo in the construction of the 2GW Bellefield project in Kern County, California – the largest solar-plus-storage project in the US, contracted with Amazon.

The Oak Ridge solar project in Louisiana, which also supports Amazon operations, marked a significant milestone as Maximo’s first utility-scale deployment.

Maximo has installed 10MW of solar capacity and is projected to install 100MW by 2025.

Maximo will assist in building 5GW of its AES’s solar backlog and pipeline up to 2027.

AES president and CEO Andrés Gluski stated: “Maximo is the first proven solar installation robot on the market.

“We are facing unprecedented increases in demand, driven in large part by the rise of AI and data centres, and innovations like these will be fundamental for accelerating our ability to bring projects online faster and with greater efficiency.”