“Human dexterity and the instinctive understanding of how to handle different objects is one of the most difficult things to replicate in industrial-grade robotics, but it’s a fundamental need for truly autonomous and versatile robots,” said Marc Segura, president of ABB Robotics. “As we develop the next generation physical AI, robots will learn and understand the world as we do. This collaboration with PSYONIC will help to close the long-standing gap between human and robot dexterity, opening up new possibilities for a wide range of industries.”

Grasping and dexterity are central to ABB Robotics’ vision for Autonomous Versatile Robotics, or AVR, which refers to robots that can sense, reason, move and handle objects with precision in dynamic environments. The companies said improved dexterity also is important to the development of physical AI in industrial settings, where robotic systems must learn from real-world interaction and apply that intelligence reliably.

The collaboration will explore applications in automotive, aerospace, packaging, life sciences and other industries. ABB Robotics and PSYONIC said the work could help robots handle repetitive, ergonomically challenging or inconsistent tasks while improving productivity, flexibility and workplace safety.

PSYONIC is working with ABB Robotics’ research and development team on integration and development of touch-enabled manipulation for autonomous robotics applications.

The PSYONIC Ability Hand was originally developed for prosthetic use. It combines myoelectric control, touch sensing and compliant mechanics in a lightweight, multi-articulating design. Its pressure sensors and vibration feedback system allow users to detect contact, grip force and release, while flexible fingers conform to irregular and deformable objects.

“Dexterous manipulation is ultimately a data challenge as much as a hardware challenge,” said Dr. Aadeel Akhtar, founder and CEO of PSYONIC. “By using the same Ability Hand on people and on robots, we can capture high-fidelity real-world data on movement, contact and grip force, then use that to train robotic systems more effectively. Integrating with ABB Robotics’ robotics platform allows us to expand into more environments and unlock the level of dexterity needed to take on the hardest challenges in automation.”

ABB Robotics said the GoFa cobot provides the accuracy and repeatability needed to evaluate subtle variations in grip force, finger positioning and motion. The companies said that precision is important for translating human-derived manipulation data into reliable robotic performance across complex tasks.

The collaboration will evaluate industrial use cases where traditional grippers struggle with variability, fragility or complexity, including the handling of irregular or delicate objects.

According to the International Federation of Robotics, advanced gripping and digital integration can reduce engineering time by up to 30%.