Abstract
One of the main problems in robotics is the Inverse Kinematics (IK) problem. In this paper, three optimization algorithms are proposed to solve the IK of Humanoid Robotic Arms (HRAs). A Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), and Black Hole Optimization (BHO) algorithms are proposed in order to optimize the parameters of the proposed IK. Also, in this paper, each optimization method is applied on both right and left arms to find the desired positions and required angles with a minimum error. Denavit-Hartenberg (D-H) method is used to design and simulate the mathematical model of HRAs for both arms in which each arm has five Degree Of Freedom (DOF). The HRAs model is tested for performance by several positions to be reached by both arms in the same time to find which optimization algorithm is better. Optimal solution obtained by SSO, PSO and BHO algorithms are evaluated and listed in comparison table between them. These optimization algorithms are assessed by calculating the Computational Time (CT) and Root Mean Squared Error (RMSE) for the absolute error vector of the positions. Calculation and simulation results showed that BHO algorithm is better than the other optimization algorithms from point of view of CT and RMSE. The worst RMSE is 0.0864 was calculated using PSO algorithm. But longer CT is 7.6521 second, which was calculated using SSO. While the best RMSE and shorter CT.are and 3.0156 second respectively were calculated by BHO algorithm. Moreover, in this paper, the Graphical User Interface (GUI) is designed and built for motional characteristics of the HRAs model in the Forward Kinematics (FK) and IK. The optimization algorithms are designed using MATLAB package facilities to simulate the HRAs model and the solution of IK problem.
Highlights
Inverse Kinematics (IK) solution is significant for humanoid robot interactions, for applications like teaching a robot to execute a series of coordinated gestures or telesurgery applications
The minimum values of Root Mean Squared Error (RMSE) and Computational Time (CT) are calculated in this case using Black Hole Optimization (BHO) algorithm
Through the results, we notice that the Social Spider Optimization (SSO) algorithm was a case in the between of the two other optimization algorithms in the calculation of RMSE but Particle Swarm Optimization (PSO) is better than SSO in CT
Summary
IK solution is significant for humanoid robot interactions, for applications like teaching a robot to execute a series of coordinated gestures or telesurgery applications. The researchers in [10] presented the BHO algorithm to optimize the parameter of the nonlinear controller They showed the efficiency of that optimization algorithm and nonlinear controller for solving different problems of nonlinear models. Three optimization algorithms are proposed to obtain an IK solution for both arms to reach the desired position by determining the optimal angles of the HRAs model with a minimum error. The main contribution of this paper is to reach the end effector of each arm with higher accuracy to control both arms at the same time and found which optimization technique has a minimum error and less CT which is the length of time required to perform a computational optimization algorithm.
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