Improving Grasping Performance of Underactuated Two Finger Robotic Hands Using Variable Stiffness

In this work, we aim to improve the performance of an underactuated anthropomorphic tendon driven robotic gripper with two fingers by allowing the stiffness of the finger joints to change as a function of the object shape. An optimization problem requiring that the gripper apply a constant total contact force with a minimum actuation force was formulated using a Genetic Algorithm (GA) approach in order to obtain a set of designs with geometrical parameters such as position and size of various elements of the fingers as well as stiffness of the joints. The optimization process was also repeated for the fixed stiffness case to compare the two approaches, demonstrating that the addition of variable stiffness allowed to achieve the same grasp with less actuation force.