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Robot Touch: Bionic Hands Teach Robots to Feel
25 Jun
Summary
- Robots are being trained using touch data from prosthetic hands.
- This collaboration aims to improve robot dexterity with human-like control.
- The technology could enhance handling of delicate and variable objects.
ABB Robotics and PSYONIC are pioneering a new method to improve robot dexterity by utilizing real-world touch and motion data from prosthetic hands. This collaboration aims to train robotic arms to handle delicate or unpredictable objects with greater precision and human-like control.
The project integrates PSYONIC's Ability Hand, equipped with advanced sensors and flexible mechanics, with ABB's GoFa cobot. By capturing grip-force and contact data from prosthetic users, the initiative seeks to generate natural datasets that will teach robots nuanced manipulation skills.
This advancement addresses a significant challenge in industrial automation, where robots often struggle with tasks requiring subtle touch. The technology holds potential applications across various sectors, including automotive, aerospace, and logistics, promising to reduce engineering time and enable more flexible automation.
While enhancing robotic capabilities, the development also raises questions about the future of factory work. The aim is for these advanced robots to support human workers, allowing people to focus on oversight and higher-skilled tasks rather than repetitive, strenuous motions.
