Solving the forward kinematics problem in parallel robots using Support Vector Regression

Morell, Antonio; Tarokh, Mahmoud; Sánchez, Leopoldo

doi:10.1016/j.engappai.2013.03.011

Cited by 51 publications

(37 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Polynomial learning networks (PLN) have been proposed by Boudreau, and results show that PLN can generate good accuracy [21]. The Support Vector Machines (SVM) method has also been proposed to investigate the FKP of parallel mechanisms by Zhang and Morell [22,23].…”

Section: Nn Approachesmentioning

confidence: 98%

“…Various numerical approaches have been studied in Refs. [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] to obtain fast and efficient FKP solutions for parallel mechanisms. These approaches include iterative approaches, polynomial approximation approaches, optimization algorithmbased approaches, and neural network (NN)-based approaches.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Real-time solution of the forward kinematics for a parallel haptic device using a numerical approach based on neural networks

et al. 2015

View full text Add to dashboard Cite

This paper proposes a neural network (NN)-based approach to solve the forward kinematics of a 3-RRR spherical parallel mechanism designed for a haptic device. The proposed algorithm aims to remarkably speed up computation to meet the requirement of highfrequency rendering for haptic display. To achieve high accuracy, the workspace of the haptic device is divided into smaller subspaces. The proposed algorithm contains NNs of two different precision levels: a rough estimation NN to identify the index of the subspace and several precise estimation networks with expected accuracy to calculate the forward kinematics. For continuous motion, the algorithm structure is further simplified to save internal memory and increase computing speed, which are critical for a haptic device control system running on an embedded platform. Compared with the mostly used Newton-Raphson method, the proposed algorithm and its simplified version greatly increase the calculation speed by about four times and 10 times, respectively, while achieving the same accuracy level. The proposed approach is of great significance for solving the forward kinematics of parallel mechanism used as haptic devices when high update frequency is needed but hardware resources are limited.

show abstract

Section: Nn Approachesmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Real-time solution of the forward kinematics for a parallel haptic device using a numerical approach based on neural networks

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Guan et al [13] use neural networks to design a hybrid computational intelligent method for the kinematic analysis of the parallel machine tool. Morella et al [15] proposed a support vector machine to solve the forward kinematics problems of a parallel manipulator called Stewart platform. In this paper, two models are proposed to estimate the PKM Tricept kinematic equations.…”

Section: Introductionmentioning

confidence: 99%

Kinematic Synthesis of Parallel Manipulator via Neural Network Approach

Ghasemi

Moradinezhad

Hosseini

2017

IJE

View full text Add to dashboard Cite

In this research, Artificial Neural Networks (ANNs) have been used as a powerful tool to solve the inverse kinematic equations of a parallel robot. For this purpose, we have developed the kinematic equations of a Tricept parallel kinematic mechanism with two rotational and one translational degrees of freedom (DoF). Using the analytical method, the inverse kinematic equations are solved for specific trajectory, and used as inputs for the applied ANNs. The results of both applied networks (Multi-Layer Perceptron and Redial Basis Function) satisfied the required performance in solving complex inverse kinematics with proper accuracy and speed.

show abstract

“…Subtracting equation (22) from equation (23) and equation (22) from equation (24), the following two equations are obtained, which eliminated variable z, and we get the following equations in variables x and y…”

Section: Polynomial Solutions For the Fpksmentioning

confidence: 99%

“…The numerical methods [18][19][20][21][22][23][24] were introduced to overcome this problem, such as Newton-Raphson method, continuation methods, neural networks, genetic algorithms, interval analysis, and alternative approach. Although numerical methods are accurate and can provide unique solution to the forward kinematics problem, the main challenge such as Newton-Raphson method is difficult to ascertain the number of iterations and to select the initial estimation of the task space, while some of these approaches rely on powerful computer hardware.…”

Section: Introductionmentioning

confidence: 99%

Forward kinematics solutions of a special six-degree-of-freedom parallel manipulator with three limbs

Gao

Pan

et al. 2015

Advances in Mechanical Engineering

View full text Add to dashboard Cite

This article presents a special 6-degree-of freedom parallel manipulator, and the mechanical structure of this robot has been introduced; with this structure, the kinematic constrain equations are decoupled. Based on this character, the polynomial solutions of the forward kinematics problem are also presented. In this method, the closed-loop kinematic chain of the manipulator is divided into two parts, the solution forward position kinematics is obtained by a first-degree polynomial equation first, and then an eighth-degree polynomial equation in a single variable for the forward orientation kinematics is obtained. Based on those solutions, the configurations of the robot, including position and orientation of the end-effector, are graphically displayed. A numerical simulation is given to verify the algorithm, and the result implies that for a given set of input values, the manipulator can be assembled in eight different configurations at most. And a set of experiments illustrate the motion ability for forward kinematics of the prototype of this manipulator.

show abstract

Solving the forward kinematics problem in parallel robots using Support Vector Regression

Cited by 51 publications

References 22 publications

Real-time solution of the forward kinematics for a parallel haptic device using a numerical approach based on neural networks

Real-time solution of the forward kinematics for a parallel haptic device using a numerical approach based on neural networks

Kinematic Synthesis of Parallel Manipulator via Neural Network Approach

Forward kinematics solutions of a special six-degree-of-freedom parallel manipulator with three limbs

Contact Info

Product

Resources

About