Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—In this research, Particle Swarm Optimization (PSO), Differential Evolution (DE) Algorithm and Searching Space improving DE & PSO Algorithm will be used for inverse kinematic solution of a 7-degree-of-freedom (DOF) serial manipulator. Firstly, the DH parameters of the robot manipulator are created, and transformation matrices are revealed. Afterward, the position equations are derived from these matrices. The end-effector position in the working space of the robotic manipulator is estimated using optimization algorithms. These algorithms were tested with two different end-effector motion scenarios. The first scenario uses 100 randomly selected points in the working space. The second scenario uses a spline trajectory including 100 points in the working space as well. According to the results, DE Algorithms has performed much more efficient than standard PSO Algorithms. The DE & PSO Algorithm using Searching Space Improvements can be used to optimize robots control easily.
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