A Comprehensive Research on The Use Of Swarm Algorithms in The Inverse Kinematics Solution

Dereli, Serkan; Köker, Raşit; Öylek, İsmail; Ay, Mükremin

doi:10.2339/politeknik.374830

Cited by 7 publications

(6 citation statements)

References 20 publications

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“…Both algorithms could get the appropriate solutions, but ANFIS algorithm proved to be the best one. The comparison also shows that a number of studies [12,22,23], using optimal algorithms such as PSO, ABC, Q-PSO … handle the inverse kinetic requirements for the model of 7 degrees of freedom. All the used algorithms have proven the ability to handle the problem, but it is not difficult to see that most of these studies have the lower accuracy and processing speed than the ISADE as well as the Pro-ISADE algorithm proposed in this study.…”

Section: Scenario 3 Resultsmentioning

confidence: 89%

“…In Scenario 2, the end effector moved through the 100 points located on a specific trajectory that was defined in Eq. (22) and shown in Figure 3b. The main difference between Scenario 2 and Scenario 3 is that, instead of after solving each IK problem for each point, the end effector goes back to the original point to continue processing for the next points like in Scenario 2, in Scenario 3 the end effector starts from previous point in order to calculate for the next point.…”

Section: Scenario 3 Resultsmentioning

confidence: 97%

See 1 more Smart Citation

Use Improved Differential Evolution Algorithms to Handle the Inverse Kinetics Problem for Robots with Residual Degrees of Freedom

Nguyen¹,

Bui²

2021

Robotics Software Design and Engineering

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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.

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Section: Scenario 3 Resultsmentioning

confidence: 89%

Section: Scenario 3 Resultsmentioning

confidence: 97%

Use Improved Differential Evolution Algorithms to Handle the Inverse Kinetics Problem for Robots with Residual Degrees of Freedom

Nguyen¹,

Bui²

2021

Robotics Software Design and Engineering

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“…Its solution enables the robot to realize kinematic simulation and trajectory planning. 23 Because the inverse solution of the collaborative robot is difficult to obtain, the inverse kinematics model is analyzed using a combination of a closed-form solution and numerical solution. The Manocha elimination method was used to determine the forward kinematics, and the key matrix of the inverse kinematics was obtained using singular value decomposition (SVD) and the Newton-Raphson iteration method.…”

Section: Inverse Kinematics Modellingmentioning

confidence: 99%

Combining closed-form and numerical solutions for the inverse kinematics of six-degrees-of-freedom collaborative handling robot

Chen,

Cui,

Wang

et al. 2024

International Journal of Advanced Robotic Systems

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In the process of solving the inverse kinematics of six-degrees-of-freedom collaborative robots, the numerical solution has problems such as low accuracy and singular configurations. Moreover, due to the high coupling of its position and attitude, the direct closed-form solution fails. To address these problems, an inverse kinematics algorithm that combines closed-form and numerical solutions was proposed. The Jacobian matrix was established based on the forward kinematics equation of the six-degrees-of-freedom collaborative robot. Its inverse matrix was obtained by a singular value decomposition of the matrix using the Manocha elimination method to avoid the singularities of the Jacobian matrix. The optimal inverse kinematics solution was obtained using the Newton–Raphson iterative method. A computer simulation implemented in MATLAB and Visual C++ was used to evaluate the accuracy and speed of the proposed algorithm. The results of the trajectory planning experiments demonstrate that the algorithm satisfies the requirements for real-time smooth motion. This study of inverse kinematics lays the theoretical foundation for solutions to the inverse problem and real-time control of collaborative robots.

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“…The firefly parameters used are γ, α, β 0 , and δ known as light absorption coefficient, mutation coefficient, attraction coefficient base value, and uniform mutation range respectively. α_damp is the mutation coefficient damping ratio [16], [17], [29]. The values of these parameters can be assumed using different combinations of values at different iterations.…”

Section: Fig3: Workpace (Articulated Arm)mentioning

confidence: 99%

Kinematics Analysis of 5R axis using Evolutionary Algorithms

Kumar*¹,

Kumar²,

Kumar³

2019

IJRTE

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In this paper, we have represented the kinematics solution of five degrees of freedom articulated arm with five revolute joints using Evolutionary algorithm. DH parameters are used to obtain the kinematics analysis of the manipulator. Simulations are performed on the MATLAB to show the workspace of the robotic manipulators. Firefly and artificial bee colony algorithms (ABC) have been used for the minimization of errors. The position error and absolute error have been minimized to the acceptable level.

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A Comprehensive Research on The Use Of Swarm Algorithms in The Inverse Kinematics Solution

Cited by 7 publications

References 20 publications

Use Improved Differential Evolution Algorithms to Handle the Inverse Kinetics Problem for Robots with Residual Degrees of Freedom

Use Improved Differential Evolution Algorithms to Handle the Inverse Kinetics Problem for Robots with Residual Degrees of Freedom

Combining closed-form and numerical solutions for the inverse kinematics of six-degrees-of-freedom collaborative handling robot

Kinematics Analysis of 5R axis using Evolutionary Algorithms

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