Design and Optimization of Coupled and Self-Adaptive of An Underactuated Robotic Hand Using Particle Swarm Optimization

Abstract

A large work has been devoted to create and design the novel underactuated robotic hand that mimic human hand in terms of motion and grasps. The objective of this paper is to design and development of four-finger underactuated robotic hand mechanisms with 2-DOF for each finger that is highly underactuated which controlled by single actuator that can be used with wide applications. The principle of this hand mechanism is to use the linkage seesaw differentials and the design of robotic finger integrates segments by pin joints and a tendon, that allowing it easily of grasping and adaptable different objects. Furthermore, the robotic finger was designed with combines advantages of the concept of rigid coupled and selfadaptive into one unit to achieve better performance with simple design. To plan the trajectory of the robotic finger and force-isotropic that resembled the human finger in motion and grasping operation, Underactuated finger mechanism was preliminary analysis to predict the relationship between the joint angles of robotic finger related to mechanical parameters as well as contact forces then, modified by optimized set of parameters using particle swarm optimization (PSO). Where, the parameter design constraints were formulated for a multi objective optimization problem using the evaluation criteria for human finger in motion and grasping. Experiments were conducted in order to validate the theoretical analysis by addition of angles sensors on each segment of fingers and the results show that the proposed hand is able to mimic human hand in terms of motion and adaptive grasps.