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The American Bureau of Shipping (ABS) and robotics innovator Persona AI have formalised a memorandum of understanding to develop humanoid inspection technologies for shipyards.
The agreement aims to use Persona AI’s intelligent humanoid platform, built in part on NASA’s robotic hand technology, to perform complex tasks in confined and ergonomically challenging shipyard environments.
Unlike fixed industrial arms, humanoid robots can navigate facilities designed for human workers, offering greater flexibility for welding, non-destructive testing and structural surveys.
Under the MOU, ABS and Persona AI will run joint development projects to gather and analyse robotic data during vessel construction, informing classification decisions and digital survey methods.
The collaboration will set new ABS standards on the quality and types of data required for remote and automated surveys, and will guide future robot design, ensuring compliance with ABS’s safety and certification frameworks.
“ABS is proud to lead the way in advancing the safe integration of emerging technologies into the maritime industry,” said ABS President and COO, John McDonald. “This collaboration with Persona AI reflects our commitment to innovation and safety, as we work to establish the standards and protocols that will enable humanoid robots to perform complex tasks reliably and securely in shipyard environments. By combining cutting-edge robotics with ABS’s deep expertise in certification and safety, we’re helping shape a smarter, safer future for shipbuilding”.
“This marks a defining moment for the shipbuilding industry,” said CEO and co-founder of Persona AI, Nic Radford. “Partnering with ABS, the global authority on maritime standards, demonstrates that humanoid robotics are no longer a distant concept but on a path toward certified reality—set to transform how this industry builds, innovates and competes”.
ABS will leverage its extensive investments in AI-driven data evaluation to support persona-driven inspections, while Persona AI will validate its systems against rigorous classification criteria.
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