Abstract
This paper addresses the complex task of unscrewing and screwing objects with a dexterous anthropomorphic robotic hand in two cases: with the first finger and thumb and also with the little finger and thumb. To develop an anthropomorphic solution, human finger synergies from nine test subjects were recorded while unscrewing and screwing a threaded cap. Human results showed that the periodic motions exhibited by the finger joints shared a common frequency for each subject, but differed in amplitude and phase. From the gathered data, a set of sinusoidal trajectories were developed to approximate this motion for application to a robotic hand. Because the joint trajectories exhibited the same frequency, a family of sinusoids that share a common time vector can be used in the path planning of the robotic hand to unscrew and screw objects. Additionally, the human unscrewing data are highly similar to the mirror image of the screwing data. This chiastic trait enables screwing to be performed by decreasing the time vector; increasing the time vector produces unscrewing. These factors significantly reduce the computational cost and complexity of the task. Cartesian and joint space error analyses show that the developed sinusoidal trajectories closely mimic the motion profiles seen in the human experiments. Furthermore, this bioinspired sinusoidal solution is extended to objects with wide variations in diameters by relating joint angle offsets of the robotic hand to object diameter size through the forward kinematics equations. The sinusoidal trajectories are all implemented within a PID sliding mode controller for a dexterous artificial hand to ensure overall system stability. Using the bioinspired sinusoidal joint angle trajectories, the robotic hand successfully unscrewed and screwed four different objects in all trials conducted with each object diameter size.
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