A robotic hand can pick up 24 different objects with human-like movements that emerge spontaneously, thanks to compliant materials and structures rather than programming.
When you reach out your hand to grasp an object like a bottle, you generally don't need to know the bottle's exact position in space to pick it up successfully. But as EPFL researcher Kai Junge explains, if you want to make a robot that can pick up a bottle, you must know everything about the surrounding environment very precisely.
In a series of experiments, the ADAPT hand, which can be controlled remotely, was able to pick up 24 objects with a success rate of 93%, using self-organized grasps that mimicked a natural human grasp with a direct similarity of 68%. The research has been published inWhile a traditional robotic hand would need a motor to actuate each joint, the ADAPT hand has only 12 motors, housed in the wrist, for its 20 joints.
Now that this has been demonstrated systematically, the EPFL team is building on the potential of compliance by re-integrating elements of closed-loop control into the ADAPT hand, including sensory feedback -- via the addition of pressure sensors to the silicone skin -- and artificial intelligence. This synergistic approach could lead to robots that combine compliance's robustness to uncertainty, and the precision of closed-loop control.
Engineering Engineering And Construction Technology Robotics Artificial Intelligence Neural Interfaces Computer Programming
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