Mechanical Engineering Faculty Research


Grasp-Dependent Slip Prevention for a Dexterous Artificial Hand via Wrist Velocity Feedback Read More:

Document Type


Publication Date

Summer 5-22-2014


A proportional controller is compared to a nonlinear backstepping controller with four different grasps for a dexterous anthropomorphic hand. A bioinspired grasp-dependent control scheme which autonomously modulates the grip force using wrist velocity feedback to prevent grasped object slip is also introduced. Four different grasp types are evaluated to illustrate how the wrist velocity feedback architecture must differ depending upon the manner in which objects are grasped. The backstepping controller can successfully increase grip force with wrist velocity in a robustly stable bioinspired fashion. Experimental results show that the developed backstepping controller improves the position tracking abilities for multiple periodic inputs, as well as reduces step input overshoot. The slip prevention capabilities of the backstepping controller are also demonstrated and compared to the proportional control scheme. Results of the slip prevention experiments show that both the grasp type and manipulator orientation with respect to gravity are significant factors in the performance of the controllers. The backstepping control scheme significantly improves slip prevention of grasped objects for multiple grasps and in two different orientations with respect to gravity. Read More:

Publication Title

International Journal of Humanoid Robotics