Robots have become proficient in performing repetitive tasks, but they often struggle with delicate or variable handling. A new collaboration between ABB Robotics and PSYONIC aims to change this by using real-world touch and motion data from human prosthetic use to train robotic arms.
How it Works
The Ability Hand, developed by PSYONIC, is a bionic hand that helps people grip tools, pick up fragile objects, and adjust pressure in real-time. By using this hand, researchers can capture detailed data about movement, contact, and grip force, which can then be used to train robots.
ABB’s GoFa cobot is being used to test these movements in a controlled environment, with the goal of creating a robot arm that can learn from human handling data and apply it to factory and warehouse tasks. This technology has the potential to reduce strain on workers, allowing them to focus on higher-skill tasks while robots handle repetitive or ergonomically challenging work.
Implications
The development of touch-enabled robotic hands could have significant implications for various industries, including automotive, aerospace, packaging, logistics, and life sciences. By improving the ability of robots to handle fragile or variable objects, companies could deploy robots more efficiently and effectively, reducing the need for manual labor in certain tasks.
Original reporting: Fox News (HLL/CB) — read the source article.
