Dexterous Robotic-Hand Grasp Learning Using Piecewise Linear Dynamic Systems Model
Learning from sensor data plays an important role in the field of robotic research, especially in dexterous robotic hand grasping. The manuscript puts efforts on learning from tactile dynamic process during robotic hand grasping. A piecewise linear dynamic systems and a group of models are presented, under the guidance of which, proper gesture according to different types of targets could then be selected to facilitate stable and accurate grasping. This is evaluated on the experimental testbed and shows promising results.
This work was jointly supported by Tsinghua Self-innovation Project (Grant No. 20111081111) and the National Natural Science Foundation of China (Grants No. 61210013, 61075027).
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