Towards Autonomous Grasping with Robotic Prosthetic Hands

Abstract

For an effective use of a robotic prosthetic, smooth transition between the states of this human-in-the-loop cyber-physical system (or autonomous operation) is crucial. In order to achieve that, taking into account the uncertainties in the robotic system may be as significant as anticipating the human intent. In this study, we present two risk measures associated with a simple grasping task based on the pre-grasp position and orientation of the robotic hand, and analyze them by using a model of a dexterous mechatronic prosthetic arm to simulate a simple grasping task. Moreover, we develop a hybrid position and force grasp controller and use a grasp quality metric to assess the grasps. 34 simulations with different pre-grasp poses were performed to investigate the relationship between the grasp quality and the risk measures as well as the sensitivity of the grasp quality to the pre-grasp position of the hand. Results show that the proposed risk metrics and the pre-grasp position correlate with the grasp quality, yet they are not sufficient to predict the outcome.