Abstract
In this paper, we address the forward kinematics solution of 6DOF 6 × 6 UPU parallel mechanism using three different approaches. In contrast to the case of serial robots, the forward kinematics of parallel manipulators contain highly coupled nonlinear equations which are possible to solve analytically only in very special cases. In the proposed paper, Adaptive-Network-based Fuzzy Inference System (ANFIS), Multilayer Perceptron (MLP) and Radial Base Function (RBF) Neural Network methods are implemented to reach the forward kinematics solution of a low payload flight simulator. Solution accuracies have been compared, and it has been concluded that ANFIS shows better performance compared to MLP and RBF networks.
Keywords
Kinematics
Adaptive neuro fuzzy inference system
Forward kinematics
Computer science
Artificial neural network
Multilayer perceptron
Control theory (sociology)
Nonlinear system
Payload (computing)
Artificial intelligence
Kinematics equations
Mechanism (biology)
Parallel manipulator
Simulation
Robot
Robot kinematics
Fuzzy logic
Inverse kinematics
Fuzzy control system
Mobile robot
Subject Areas
Robotic Mechanisms and Dynamics
·Control and Systems Engineering ·Physical Sciences
Robot Manipulation and Learning
·Control and Systems Engineering ·Physical Sciences
Iterative Learning Control Systems
·Control and Systems Engineering ·Physical Sciences
Citations by Year
2022: 1
2023: 1
2025: 1
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