Inverse Kinematics Of Manipulator Research Articles

Improved Artificial Potential Field Method Manipulator Inverse Kinematics

The use of traditional analytical method for manipulator inverse kinematics is able to get a display solution with the limitations of the application, only when the robotic arm has a specific structure. In view of the insufficient, this paper presents an improved artificial potential field method to solve the inverse kinematics problem of the manipulator which does not have a special structure. Firstly, establish the standard DH model for the robot arm. Then the strategy that improves search space of artificial potential field method and motion control standard is presented by combining artificial potential field method with the manipulator. Finally, the simulation results show that the proposed method is effective.

Kinematical Analysis on Three-DOF Cylindrical Industrial Manipulator

Base on robot D-H method, the features of three-DOF cylindrical industrial manipulator are analyzed, the motion equation of robotic mechanisms are deduced by using coordinate transformation method and symbolic method. Then three-DOF cylindrical industrial manipulator inverse kinematics solving analytic formula is found. That provides a basis for the position and speed control of actual three-DOF cylindrical industrial manipulator.

Solution for a New Sub-Problem in Screw Theory and its’ Application in the Inverse Kinematics of a Manipulator

Three basic sub-problems of screw theory are acceptable for some particular configuration manipulators’ inverse kinematics, which can not solve the inverse kinematics of all configuration manipulators. A new sub-problem is presented and the inverse kinematics thereof is solved in this paper. Based on the extended sub-problem, a manipulator, the inverse kinematics of which can not be solved by the three sub-problems without the participation of the new sub-problem, is constructed. The inverse kinematics of the manipulator is solved with the help of the extended sub-problem。Therefore a close solution is gained. The sub-problem herein can be applied directly in the inverse kinematics of a manipulator, providing a new approach for the inverse kinematics of a general configuration manipulator.

An adaptive niching genetic algorithm approach for generating multiple solutions of serial manipulator inverse kinematics with applications to modular robots

SUMMARYInverse kinematics (IK) is a nonlinear problem that may have multiple solutions. A modified genetic algorithm (GA) for solving the IK of a serial robotic manipulator is presented. The algorithm is capable of finding multiple solutions of the IK through niching methods. Despite the fact that the number and position of solutions in the search space depends on the position and orientation of the end-effector as well as the kinematic configuration (KC) of the robot, the number of GA parameters that must be set by a user are limited to a minimum through the use of an adaptive niching method. The only requirement of the algorithm is the forward kinematics (FK) equations which can be easily obtained from the Denavit–Hartenberg link parameters and joint variables of the robot. For identifying and processing the outputs of the proposed GA, a modified filtering and clustering phase is also added to the algorithm. For the postprocessing stage, a numerical IK solver is used to achieve convergence to the desired accuracy. The algorithm is validated on three KCs of a modular and reconfigurable robot (MRR).

Inverse kinematics of manipulator using weighted fuzzy clustering method for fuzzy training data

The inverse kinematics of redundant manipulator is considered. A model-free regression approach based on weighted fuzzy clustering method is formulated. For the adopted technique, the observed or training data pair is fuzzy instead of crisp for known value of joint variables to enhance the practicability of inverse kinematics solutions, since the real-time data collected by the sensors is generally fuzzy or vague instead of crisp. Simulation results indicate that this method has higher identifying precision and better real-time ability. Therefore, a new way for solving the inverse kinematics of manipulator for fuzzy data is proposed.

Manipulator Inverse Kinematics using an Adaptive Back-propagation Algorithm and Radial Basis Function with a Lookup Table

This is an extension of previous work which used an artificial neural network with a back-propagation algorithm and a lookup table to find the inverse kinematics for a manipulator arm moving along pre-defined trajectories. The work now described shows that the performance of this technique can be improved if the back-propagation is made to be adaptive. Also, further improvement is obtained by using the whole workspace to train the neural network rather than just a pre-defined path. For the inverse kinematics of the whole workspace, a comparison has also been done between the adaptive back-propagation algorithm and radial basis function.

A Theoretical Research on Compensation Method for Beam End Positioning Error due to Assembling Inaccuracies in an Optical Manipulator. 1st Report. Beam End Position under the Existence of Assembling Inaccuracies.

In the case of laser cutting machine of rocking mirror type, which is newly developed and a kind of optical manipulator, the positioning error of final laser spot on cutting plane, caused by assembling inaccuracies of optical system, would inevitably exceed the allowable limit without appropriate compensation. This research aims to establish the theory on the positioning error and its compensation for this new machine, with kinematics and inverse kinematics of manipulator. In this paper, a formula of actual position of final laser spot is derived as an implicit function of aimed position and the assembling inaccuracies.

Inverse Kinematics of Binary Manipulators Using a Continuum Model

Binary actuators have only two discrete states, both of which are stable without feedback. As a result, manipulators with binary actuators have a finite number of states. The major benefits of binary actuation are that extensive feedback control is not required, reliability and task repeatability are very high, and two-state actuators are generally very inexpensive, resulting in low cost robotic mechanisms. These manipulators have great potential for use in both the manufacturing and service sectors, where the cost of high performance robotic manipulators is often difficult to justify. The most difficult challenge with a binary manipulator is to achieve relatively continuous end-effector trajectories given the discrete nature of binary actuation. Since the number of configurations attainable by binary manipulators grows exponentially in the number of actuated degrees of freedom, calculation of inverse kinematics by direct enumeration of joint states and calculation of forward kinematics is not feasible in the highly actuated case. This paper presents an efficient method for performing binary manipulator inverse kinematics and trajectory planning based on having the binary manipulator shape adhere closely to a time-varying curve. In this way the configuration of the arm does not exhibit drastic changes as the end effector follows a discrete trajectory.

Reconstruction of the inverse kinematic solution subject to joint kinematic limits using kinematic redundancy

Various physical limitations which intrinsically exist in the manipulator inverse kinematic system, e.g. joint travel and velocity limits, induce inevitable motion errors. This paper is concerned with how to reconstruct such an inverse kinematic solution using redundancy, in order not to produce any task motion error. By analyzing the error due to hardware limitations with respect to the kinematically decoupled coordinates, we are able to show that the recoverability of limitation reduces to the solvability of a reconstruction equation under the feasibility condition. It will be next shown that the reconstruction equation is solvable if the configuration is not a joint-limit singularity. The reconstruction method will be proposed based on the geometrical analysis of recoverability of hardware limitations. The method has the feature that no task motion error is induced by the hardware limitations while minimizing a possible null motion error under the recoverability assumed.

Feasibility study of manipulator inverse kinematics problems with applications of optimization principles

This paper studies three efficient methods for solving inverse kinematics problems relevant to a six-link robot manipulator. In a problem formulation, governing kinematic equations are transformed into an unconstrained optimization problem with an objective function defined by a sum of squares of the errors, and then two nonlinear models—i.e. the variable metric method and the least squares method-are applied to derive stable joint solutions together with a practical linearized model. The results of computer simulation show that these numerical solutions are highly reliable over a much wider application range as compared with a traditional method.

A fast procedure for manipulator inverse kinematics computation and singularities prevention

AbstractIn this article, a fast procedure for numerical manipulator inverse kinematics computation and singularities prevention is presented. The approach is based upon solving a linear system and automatically calculating some parameters. These parameters are properly used in either one of two original schemes that are also proposed to induce robustness to the pseudoinverse. Furthermore, here it is also shown how to properly implement one of these schemes in conjunction with a recently developed approach for the singularities prevention of redundant manipulators. The resultant algorithms are tested on the simulation of a planar redundant manipulator. From the results obtained, it is observed that the proposed approach compares favorably with the approaches using a Gaussian elimination procedure and with pseudoinverse robustness based on a manipulability measure.

Iterative inverse kinematics with manipulator configuration control

A new method, termed the offset modification method (OM method), for solving the manipulator inverse kinematics problem is presented. The OM method works by modifying the link offset values of a manipulator until it is possible to derive closed-form inverse kinematics equations for the resulting manipulator (termed the model manipulator). This procedure allows one to derive a set of three nonlinear equations in three unknowns that, when numerically solved, give an inverse kinematics solution for the original manipulator. The OM method can be applied to manipulators with any number of degrees of freedom, as long as the manipulator satisfies a given set of conditions (Theorem 1). The OM method is tested on a 6-degree-of-freedom manipulator that has no known closed-form inverse kinematics equations. It is shown that the OM method is applicable to real-time manipulator control, can be used to guarantee convergence to a desired endpoint position and orientation (if it exists), and allows one to directly choose which inverse kinematics solution the algorithm will converge to (as specified in the model manipulator closed-form inverse kinematics equations). Applications of the method to other 6-DOF manipulator geometries and to redundant manipulators (i.e. greater than 6 DOF geometries) are discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Procedure for manipulator inverse kinematics computation and proper pseudoinverse perturbation

In this article, an efficient procedure for the proper pseudoinverse perturbation and the numerical inverse kinematics computation of robot manipulators is presented. The approach is based on solving a linear system of equations and using an original scheme for the appropriate perturbation of the pseudoinverse matrix in the next iteration. The resultant algorithm is tested on the simulation of an industrial robot manipulator. From the results obtained, it is observed that the proposed approach compares favorably with the approaches using a Gaussian elimination procedure and with pseudoinverse robustness based on a manipulability measure.

A fast procedure for manipulator inverse kinematics evaluation and pseudoinverse robustness

A fast procedure for the computation of manipulator inverse kinematics and pseudoinverse robustness is presented. The approach is based on solving a linear algebraic system and evaluating the norm of the Jacobian matrix. This value is properly used in an original scheme that is also proposed for the appropriate robustness of the pseudoinverse matrix. The developed algorithm is tested on the simulation of a planar redundant manipulator and of an industrial robot arm. From the results obtained it is observed that the proposed approach compares favorably with the approaches using a Gaussian elimination procedure and with pseudoinverse robustness based on a manipulability measure.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Neutral learning of constrained nonlinear transformations

Two issues that are fundamental to developing autonomous intelligent robots, namely rudimentary learning capability and dexterous manipulation, are examined. A powerful neural learning formalism is introduced for addressing a large class of nonlinear mapping problems, including redundant manipulator inverse kinematics, commonly encountered during the design of real-time adaptive control mechanisms. Artificial neural networks with terminal attractor dynamics are used. The rapid network convergence resulting from the infinite local stability of these attractors allows the development of fast neural learning algorithms. Approaches to manipulator inverse kinematics are reviewed, the neurodynamics model is discussed, and the neural learning algorithm is presented. >

Manipulator Inverse Kinematic Solutions Based on Vector Formulations and Damped Least-Squares Methods

Inverse kinematic solutions are used in manipulator controllers to determine corrective joint motions for errors in end-effector position and orientation. Previous formulations of these solutions, based on the Jacobian matrix, are inefficient and fail near kinematic singularities. Vector formulations of inverse kinematic problems are developed that lead to efficient computer algorithms. To overcome the difficulties encountered near kinematic singularities, the exact inverse problem is reformulated as a damped least-squares problem, which balances the error in the solution against the size of the solution. This yields useful results for all manipulator configurations.