Torfresma
Plus One Robotics and Torfresma are showcasing AI-powered depalletizing and palletizing automation at PACK EXPO 2026.
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Torfresma
Plus One Robotics and Torfresma are showcasing AI-powered depalletizing and palletizing automation at PACK EXPO 2026.
Plus One Robotics is showcasing its latest depalletizing and palletizing capabilities at PACK EXPO 2026 in Chicago.
In partnership with automation hardware provider Torfresma, Plus One said that it is demonstrating a live depalletizing and palletizing cell featuring Torfresma’s TRF Compact system and an ABB robot.
The companies said that the demonstration features a modular robotic cell that showcases how Plus One’s AI-powered vision technology integrates with proven automation hardware to address the variability and complexity of real-world warehouse and distribution environments.
Plus One said that the live demo highlights the role of intelligent perception and decision-making in robotic material handling, showing how robots can identify and respond to products as they move through automated workflows. The companies said their collaboration also underscores the value of pairing specialized robotics technology with established hardware platforms to create practical and scalable automation.
“The industry is moving quickly toward more intelligent robots, but the measure of success is still pretty simple: does the system work reliably, and can it deliver value for the customer,” said Erik Nieves, CEO of Plus One Robotics. “Getting robots to work in the real world is about much more than making a robot move or giving it an AI model. You have to bring the computer vision, the hardware, the software and the human expertise together in a system that can reliably handle what actually happens on the warehouse floor. That’s where AI and human oversight work together.”
Plus One Robotics said that its approach to automation is built around AI-powered vision and human-in-the-loop capabilities, enabling robotic systems to make decisions autonomously while maintaining access to human expertise when the system encounters an unexpected or difficult situation. The company said that this approach allows human intervention to become part of the learning and improvement process while reducing the amount of intervention required over time.
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