Gravis Robotics Launches US Expansion: How Autonomous Construction Reshapes PLC Markets
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Gravis Robotics Launches US Expansion: How Autonomous Construction Reshapes PLC Markets
In a landmark announcement that signals the maturation of construction automation, Gravis Robotics has launched its full commercial expansion into the United States market. The company's debut of Gravis Copilot at CONEXPO-CON/AGG 2026 in Las Vegas represents more than just another product launch, it marks a fundamental shift in how heavy industry approaches automation and control systems.
Detail
The timing couldn't be more critical. With the construction industry projected to need 349,000 additional skilled laborers in 2026 in the U.S. alone, according to Associated Builders & Contractors, automation solutions are no longer optional luxuries but essential tools for maintaining productivity and competitiveness.
What makes Gravis Copilot particularly significant for industrial automation professionals is its platform architecture. Built on Gravis' perception and compute RACK (rooftop autonomous control kit), every machine equipped today is autonomy-ready. This means contractors can unlock fully autonomous tasks, such as trenching and truck loading, with a simple software upgrade.
"By launching Gravis Copilot at CONEXPO 2026, we're bringing that opportunity to the American jobsite, with a flexible gateway that augments all kinds of work, and that lets crews adopt autonomy at a pace that's tailored to their unique tasks and experience level," stated company representatives.
Gravis' system combines computer vision, machine learning, and ruggedized hardware to deliver safe, predictable autonomous operations across multiple OEM platforms
The Gravis RACK retrofit kit allows existing equipment to be upgraded to autonomous operation, extending machine life and ROI
Operators gain instant understanding of work requirements through integrated surveying capabilities
Autonomous systems require real-time processing of sensor data, computer vision inputs, and complex decision-making algorithms
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