National University of Singapore (NUS) engineers have constructed a robotic hand that can grasp various objects using three-dimensionally-printed fingers.
The air-driven fingers feature a locking mechanism for adjusting the level of stiffness required for grasping, while computer vision and deep learning technologies help identify object types and determine their orientation.
The system chooses the best way to pick and place objects to reduce the need for human assistance.
The NUS researchers said the gripper system may be reconfigured on demand, and can be equipped with three different grip options that permit its use in a variety of applications.
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