Researchers at Columbia University’s Robotics Group have been working on improving the grabbing dexterity of robotic hands. To this end, the researchers have been learning from the living world and limiting the domain of possible movements, therefore leading to faster, more precise electronic controls by the computer.
Here’s a snippet from MIT Technology Review:
The researchers experimented with four different kinds of complex robotic hand, each of which had multiple joints. They developed software to control each gripper by linking its joints. In simulations and real-life tests, the software was able to quickly calculate grasping positions in order to grab different objects, including a wine glass, flask, telephone, model airplane, and ashtray.
The system works in two stages. First it chooses an array of possible grasping motions depending on the angle at which the hand is approaching the object. Second, it selects from these positions the one that will provide the most stable grasp. Then, if the controller thinks the grasping position looks right, she can give the command and the hand will take hold of the object.
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