Employing Magnets to Improve the Force Exertion Capabilities of Adaptive Robot Hands in Precision Grasps Adaptive, underactuated and compliant robot hands have received an increased interest over the last decade. Possible applications of these systems range from the development of simple grippers for industrial automation to the creation of anthropomorphic devices that can be used as prosthetic hands. These hands are particularly capable of extracting stable grasps even under significant object pose or other environmental uncertainties, due to the underactuation and the structural compliance of their designs. Despite the increased interest and the promising performance, adaptive hands suffer from several disadvantages and drawbacks. For example, the use of underactuation can lead to a postcontact reconfiguration of the fingers that compromises the force exertion capabilities of the system during pinch grasping. In this paper, we focus on the design, modelling, development, and evaluation of an adaptive robot gripper that uses magnets to adjust the reconfiguration profile of the fingers. The effect of the magnets increases the gripperxe2x80x99s force exertion capabilities in pinch grasps, without compromising the full  caging grasps. The efficiency of the proposed gripper is experimentally validated through two different tests: i) a contact force test that compares the results of a theoretical model with the actual experimental results and ii) a grasping test that assesses the force exertion capabilities and the reconfiguration behaviour of the adaptive fingers for different implementations of the magnetic joints.

Nearcontact grasping strategies from awkward poses: When simply closing your fingers is not enough * Grasping a simple object from the side is easy xe2x80x94 unless the object is almost as big as the hand or space constraints require positioning the robot hand awkwardly with respect to the object. We show that humans xe2x80x94 when faced with this challenge xe2x80x94 adopt coordinated finger movements which enable them to successfully grasp objects even from these awkward poses. We also show that it is relatively straight forward to implement these strategies autonomously. Our humanstudies approach asks participants to perform grasping task by either xe2x80x9cpuppetteeringxe2x80x9d a robotic manipulator that is identical (geometrically and kinematically) to a popular underactuated robotic manipulator (the Barrett hand), or using sliders to control the original Barrett hand. Unlike previous studies, this enables us to directly capture and compare human manipulation strategies with robotic ones. Our observation is that, while humans employ underactuation, how they use it is fundamentally different (and more effective) than that found in existing hardware.