A Robot Arm Design Optimization Method by Using a Kinematic Redundancy Resolution Technique

Abstract

Redundancy resolution techniques have been widely used for the control of kinematically redundant robots. In this work, one of the redundancy resolution techniques is employed in the mechanical design optimization of a robot arm. Although the robot arm is non-redundant, the proposed method modifies robot arm kinematics by adding virtual joints to make the robot arm kinematically redundant. In the proposed method, a suitable objective function is selected to optimize the robot arm’s kinematic parameters by enhancing one or more performance indices. Then the robot arm’s end-effector is fixed at critical positions while the redundancy resolution algorithm moves its joints including the virtual joints because of the self-motion of a redundant robot. Hence, the optimum values of the virtual joints are determined, and the design of the robot arm is modified accordingly. An advantage of this method is the visualization of the changes in the manipulator’s structure during the optimization process. In this work, as a case study, a passive robotic arm that is used in a surgical robot system is considered and the task is defined as the determination of the optimum base location and the first link’s length. The results indicate the effectiveness of the proposed method.

The Study of the Dynamics of a Cebâşev Manipulator

“…A methodology for the flexible implementation of collaborative robots in intelligent manufacturing systems is presented in the paper (Giberti et al, 2022). A robot arm design optimization method using a kinematic redundancy resolution technique is presented in (Maaroof et al, 2021). Trajectory control of industrial robots using multilayer neural networks driven by iterative learning control can be found in the paper (Chen and Wen, 2021).…”