Abstract

This paper presents analysis and experiments to define object stiffness control algorithm using a prototype optical three-axis tactile sensor for improvement of dexterous grasping tasks in robotic fingers. We proposed a low force control scheme and conducted a series of calibration experiments with soft and hard objects. We analyzed normal and shearing forces data detected in the experiments. To correlate the normal force characteristics of soft and hard objects, we measured the increment of maximum normal force in specific progress time to classify the stiffness of objects. The shearing force is utilized to define re-pushes velocity of the robot fingers when grasping the object. We compiled the parameters in an algorithm inside the robot control system to control fingertips movements by defining optimum grasp pressure and perform re-push movement when slippage was detected. Verification experiments were conducted which result revealed that robot fingers managed to recognize the stiffness of objects and safely manipulate it.

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