IEEE Spectrum — Robotics · October 9, 2026 · On the brief until October 23, 2026

This Disembodied Hand Is All the Robot You Need

RoboticsMechanical Engineering

THE AI ANGLE

Training asymmetric crawling and manipulation policies through simulated reinforcement learning

Researchers at ETH Zurich turned a commercial robotic hand into a mobile robot that walks on its fingertips and moves objects. They trained the asymmetric fingers to crawl across multiple surfaces using reinforcement learning models run on a small onboard computer. The approach shows engineers can use standard manipulation hardware as standalone mobile robots for tight spaces.

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THE TEACHING ANGLE

Using a mechanism built for grasping as a walking platform forces trade-offs between delicate manipulation and joint durability under body weight loads.

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This Disembodied Hand Is All the Robot You Need

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