Iván Hernández Dalas: AES Maximo robot installs 100 megawatts of solar capacity
Maximo integrates into existing construction workflows and can double the rate of solar panel installation. Source: AES
As electricity demand grows, robot fleets must rapidly scale to help meet that need. Maximo last week said it has successfully installed 100 megawatts of utility-scale solar capacity at The AES Corp.’s Bellefield complex in Kern County, Calif. The robotics company was incubated by Arlington, Va.-based AES.
Data center expansion and the rising cost of fossil fuels are driving electrification, while the solar industry faces labor constraints, compressed project timelines, and cost volatility, according to Maximo. The startup said its 100 MW achievement marked the transition of robotic module installation from early deployment validation to sustained commercial production.
“Solar installation is one of the most repeatable construction tasks, but also physically demanding as panels get bigger,” Deise Yumi Asami, founder of Maximo, told The Robot Report. “Accelerating such repetitive activities can have an impact on schedules, and we focused on the hardest things to prove.”
Solar panels pose unique challenges for field robotics, she added. The sides are aluminum, the front is glass, and the systems must interact with these surfaces in the glare of the sun.
“Our site in California had a lot of dust and wind — there are so many things you can’t control,” said Asami. “We also had to ensure that our robotic arms could work without being on the grid.”
Maximo’s system has different modes for supervised or autonomous operation, she explained. In end-to-end mode, an operator pushes a button, and the robot does the whole installation. The system uses AI vision to adapt to variances in lighting, cell shapes, mounting structures, and configurations.
In supervised mode, the robot can place the panels with submillimeter accuracy, and people secure them to the structures, Asami said.
Bellefield site successfully shows solar installation scale
Market analysts have predicted that the U.S. will deploy hundreds of gigawatts of new solar capacity this decade. Maximo said that robotic installation allows engineering, procurement, and construction (EPC) firms to standardize installation quality while operating within complex construction environments.
By tightly integrating robotic placement into standard construction workflows, Maximo said its fleet delivered “a step change in productivity while maintaining high safety and quality standards.”
“It was an incredible experience,” said Asami. “We worked with the union and were embedded in a large-scale construction site. Normally, installing panels on 8 ft. [2.4 m] high torque tubes would require three people on ladders on uneven ground.”
The company asserted that the AES Bellefield project for Amazon demonstrated that robotics can now operate reliably at a gigawatt scale in solar construction. It grew from a single robot to a coordinated fleet of four Maximo units operating in parallel.
“We learned how to minimize changes, incorporating a process of staging where the robots go and what they do,” recalled Asami. “It’s important for us to learn fast and then focus on improving product performance and reducing tech debt. Then we can look at adding new features. We’re staying focused on the core functionality of solar module placement.”
“Reaching 100 megawatts at a single site is an important milestone for Maximo and for the role robotics can play in solar construction. It demonstrates that intelligent field robotics can deliver consistent results at utility scale,” stated Chris Shelton, president of Maximo. “As solar deployment continues to accelerate globally, technologies that improve installation speed, quality, and reliability will become increasingly important.”
Version 3.0 of the autonomous system consistently handled more than one module per minute, said Maximo. Crews installed as many as 24 modules per shift hour per person, nearly double the output of traditional installation methods in the region. The company said its upcoming release of Maximo v4.0 will build on the scale and performance success at Bellefield.
Maximo works with NVIDIA and AWS
Maximo used NVIDIA‘s AI infrastructure, Omniverse libraries, and Isaac Sim open robotics framework to develop, test, and refine its robotic fleet. The company used physics-based simulation, vision, and AI-driven modeling before deploying updates to its robots. It added that the combination of technologies reduced development and validation timelines and increased confidence in field performance, said the companies.
“Physical AI is a powerful force for accelerating real-world energy infrastructure,” said Marc Spieler, senior director of energy at NVIDIA. “By combining AI infrastructure, simulation, and edge AI, platforms like Maximo demonstrate how physical AI can help accelerate solar panel installation while maintaining high reliability in complex environments.”
In addition, Amazon Web Services (AWS) provided scalable computing, automated software delivery, and advanced data analytics, including real-time construction intelligence. This enabled Maximo to collect operational robotics data and continuously improve performance.
“By combining AI and robotics, technologies like Maximo demonstrate how we can accelerate the transition to carbon-free energy while improving safety and efficiency,” said Kara Hurst, chief sustainability officer at Amazon.
Editor’s note: Rachita Chandra, prototyping solutions architect at AWS, will present “When Language Moves Machines: The Future of Physical AI” in the Engineering Theater at the Robotics Summit & Expo. Registration is now open for the event, which will be on May 27 and 28 in Boston.
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