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—The trajectory planning of robot manipulator can be calculated by using the mathematical approach when the type of trajectories is known. However, the conventional mathematical method becomes prohibitive because of the complicated mathematical equation and derivation. This research introduces the use of artificial neural networks (ANN) to overcome these limitations by solving nonlinear functions and adapting the characteristics of trajectory planning. A virtual three-degree-of-freedom (DOF) robot manipulator is exploited in this research. The analysis and selection of hyper-parameter for ANN will go through in order to get the optimum performance for ANN. Finally, sample data will be used to evaluate the robustness of the developed ANN topology by comparing the actual results (mathematical approach) with ANN results.
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