Benchmarking the Grasping Capabilities of the iCub Hand with the YCB Object and Model Set
288 - 294
IEEE Robotics and Automation Letters
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© 2016 IEEE. The letter reports an evaluation of the iCub grasping capabilities, performed using the YCB Object and Model Set. The goal is to understand what kind of objects the iCub dexterous hand can grasp, and with what degree of robustness and flexibility, given the best possible control strategy. Therefore, the robot fingers are directly controlled by a human expert using a dataglove: in other words, the human brain is employed as the best possible controller. Through this technique, we provide a baseline for researchers who want to evaluate the performance of their grasping controller. By using a widespread robotic platform and a publicly available set of objects, we believe that many researchers can directly benefit from this resource; moreover, what we propose is a general methodology for benchmarking of grasping and manipulation that can be applied to any dexterous robotic hand.