Abstract

In this study, the Self-adaptive strategy algorithm for controlling parameters in Differential Evolution algorithm (ISADE) improved from the Differential Evolution (DE) algorithm, as well as the upgraded version of the algorithms has been applied to solve the Inverse Kinetics (IK) problem for the redundant robot with 7 Degree of Freedom (DoF). The results were compared with 4 other algorithms of DE and Particle Swarm Optimization (PSO) as well as Pro-DE and Pro-PSO algorithms. These algorithms are tested in three different Scenarios for the motion trajectory of the end effector of in the workspace. In the first scenario, the IK results for a single point were obtained. 100 points randomly generated in the robot’s workspace was input parameters for Scenario 2, while Scenario 3 used 100 points located on a spline in the robot workspace. The algorithms were compared with each other based on the following criteria: execution time, endpoint distance error, number of generations required and especially quality of the joints’ variable found. The comparison results showed 2 main points: firstly, the ISADE algorithm gave much better results than the other DE and PSO algorithms based on the criteria of execution time, endpoint accuracy and generation number required. The second point is that when applying Pro-ISADE, Pro-DE and Pro-PSO algorithms, in addition to the ability to significantly improve the above parameters compared to the ISADE, DE and PSO algorithms, it also ensures the quality of solved joints’ values.

Highlights

  • The robot Inverse Kinematics problem involves finding the joints’ variable values that match input parameters of position and direction of the end effector [1]

  • When setting up the maximum distance error by the fitness value setting for the end effector position, the study set the value of 1e À ðmÞ; 1e À ðmÞ and 1e À 17 ðmÞ for Particle Swarm Optimization (PSO) (Pro-PSO); Differential Evolution (DE) (Pro-DE) and ISADE (Pro-ISADE), respectively or that can be seen in the Table 2

  • To evaluate the effectiveness of the two algorithms above, the results obtained from the ISADE algorithm as well as Pro-ISADE were compared with the results from the PSO (ProPSO) and DE (Pro-DE) algorithm

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Summary

Introduction

The robot Inverse Kinematics problem involves finding the joints’ variable values that match input parameters of position and direction of the end effector [1]. These matched variable values will ensure that subsequent robot control will follow the desired trajectory. In recent research [9], Malek et al used PSO algorithm to handle inverse kinematics for a 7-DoF robot arm manipulator The study mentioned both the requirements for the location and the direction of the endpoint, it only solved for 2 different end effector positions. The self-adaptive control parameters in Differential Evolution (ISADE) algorithm, that developed [13, 14] by authors, was applied to solve the problem of inverse kinematic for a 7-DOF serial robot.

Testing model
SθiCαi CθiCαi ÀSαi ÀdiSαi 7
Applied algorithms and object functions
Mutation operator
Adaptive scaling factor F and crossover control parameter CR
Cost functions and Algorithms with searching space improvement
Scenario 1
Scenario 2
Scenario 3
Experimental setup
Scenario 1 results
Scenario 2 results
Scenario 3 results
Conclusions
Full Text
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