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Human Data Boosts Robot Dexterity: ABB & PSYONIC Collaboration

ABB Robotics and PSYONIC are collaborating to enhance robotic gripping, utilising human prosthetic data to train robots for complex tasks. This partnership aims to bridge the gap between human and robot dexterity, with significant implications for various UK industries.

  • ABB Robotics and PSYONIC are using human prosthetic data to improve robotic dexterity.
  • The PSYONIC Ability Hand, combined with ABB GoFa cobots, gathers real-world manipulation data.
  • This approach aims to enable robots to perform delicate and variable tasks previously difficult to automate.
  • The collaboration has potential applications across automotive, aerospace, logistics, and life sciences.
  • Improved robotic dexterity could lead to increased productivity, flexibility, and workplace safety in the UK.

A game-changing fusion between Swedish industrial giant ABB Robotics and California-based bionics firm PSYONIC is poised to give robots a significant boost in dexterity, thanks to the transfer of human-inspired data from prosthetic users. This pioneering collaboration tackles one of automation's most stubborn challenges: replicating humans' intuitive grasp on handling complex objects.

The partnership combines PSYONIC’s Ability Hand – originally designed for amputees to regain hand function – with ABB's GoFa cobots, which are already renowned for their precision. The Ability Hand is equipped with advanced myoelectric control, touch sensing, and flexible mechanics that allow it to detect contact, grip force, and release, as well as adapt its grasp to accommodate irregular shapes. By integrating this hand into robotic systems, high-quality data on movement, contact, and grip force can be collected, enabling more effective training of robots.

This initiative is a key component of ABB Robotics' vision for Autonomous Versatile Robotics (AVR™), which envisions robots capable of sensing, reasoning, moving, and handling objects with precision in dynamic environments. According to Marc Segura, President of ABB Robotics, developing the next generation of physical AI will empower robots to learn and understand the world in a human-like manner – and this collaboration is specifically aimed at bridging the dexterity gap between humans and machines.

The potential impact on various industries is substantial, with sectors such as automotive, aerospace, packaging and logistics, and life sciences set to benefit from robots taking over tasks that are currently repetitive, ergonomically challenging, or difficult to perform consistently. This promises to enhance productivity, improve flexibility in manufacturing and supply chains, and bolster workplace safety by shifting hazardous or monotonous tasks from human workers to robots.

The International Federation of Robotics (IFR) suggests that advanced gripping technologies and digital integration can reduce engineering time by up to 30%. This underscores the importance of such advancements in accelerating the deployment of automation and improving the return on investment for businesses investing in robotic solutions. The precision offered by ABB Robotics’ GoFa cobots is crucial for translating human-derived manipulation data into reliable robotic performance across complex and variable tasks.

Dr. Aadeel Akhtar, Founder and CEO of PSYONIC, highlighted that dexterous manipulation is as much a data challenge as it is a hardware one. This collaboration aims to unlock the level of dexterity needed to tackle even the most demanding automation challenges – by effectively capturing and utilising human-generated data to train robotic systems.

Source: ABB Robotics

Why this matters: This collaboration could significantly transform UK industries by enabling robots to perform more complex and delicate tasks, leading to increased efficiency and safety. It represents a stride towards more adaptable automation across various sectors.

What this means for you: What this means for you: UK consumers could benefit from more efficient production processes, potentially leading to lower costs and higher quality goods. For workers, it could mean a shift away from repetitive or dangerous tasks, with a greater focus on oversight and specialised roles.

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