scholarly journals Joint Space Redundancy Resolution of Serial Link Manipulator: An Inverse Kinematics and Continuum Structure Numerical Approach

2020 ◽  
Author(s):  
Toshit Jain ◽  
Jinesh Kumar Jain ◽  
Debanik Roy
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Complex Structure ◽  
Initial Approximation ◽  
Joint Space ◽  
Primary Objective ◽  
Target Point ◽  
Redundancy Resolution ◽  
Redundant Manipulator ◽  
Serial Link

Automatic control to any of robot manipulators, some kind of issues are being observed. A numerical method for solution generation to the inverse kinematics problem of redundant robotic manipulators is presented to obtain the smoothest algorithm as possible, leading to a robust iterative method. After the primary objective of the reachability of end-effectors to the target point is achieved, the aim is set to resolve the redundant degrees of freedom of redundant manipulator. This method is numerically stable since it converges to the correct answer with virtually any initial approximation, and it is not sensitive to the singular configurations of the manipulator. In addition, this technique is computationally effective and able to apply for serial manipulators with any DOF applications. A planar 3R-DOF serial link redundant manipulator is considered as exemplar problem for solving. Also, the continuum approach for resolving more complex structure with variable DoF is illustrated here and their brief applicability to support surgeries and adaptive use of artificial linkage moments is also calculated.

scholarly journals Redundancy Resolution Using Tractrix: Simulations and Experiments

2009 ◽  
Author(s):  
V. C. Ravi ◽  
Subrata Rakshit ◽  
Ashitava Ghosal
Keyword(s):  
Degrees Of Freedom ◽  
Redundancy Resolution ◽  
Redundant Manipulator ◽  
End Effector ◽  
Redundant Robots ◽  
Natural Motion ◽  
Fixed Base ◽  
Effective Use ◽  
Actuated Joints ◽  
Present Simulation

Hyper-redundant robots are characterized by the presence of a large number of actuated joints, many more than the number required to perform a given task. These robots have been proposed and used for many application involving avoiding obstacles or, in general, to provide enhanced dexterity in performing tasks. Making effective use of the extra degrees of freedom or resolution of redundancy have been an extensive topic of research and several methods have been proposed in literature. In this paper, we compare three known methods and show that an algorithm based on a classical curve called the tractrix leads to a more ‘natural’ motion of the hyper-redundant robot with the displacements diminishing from the end-effector to the fixed base. In addition, since the actuators at the base ‘see’ the inertia of all links, smaller motion of the actuators nearer to the base results in a smoother motion of the end-effector as compared to other two approaches. We present simulation and experimental results performed on a prototype eight link planar hyper-redundant manipulator.

scholarly journals Investigation of Cyclicity of Kinematic Resolution Methods for Serial and Parallel Planar Manipulators

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 9
Author(s):  
Maurizio Ruggiu ◽  
Andreas Müller
Keyword(s):  
Objective Function ◽  
Inverse Kinematics ◽  
Joint Space ◽  
Point Of View ◽  
Initial Configuration ◽  
Local Optimum ◽  
Closed Path ◽  
Redundancy Resolution ◽  
Projected Gradient Method ◽  
Inverse Kinematics Problem

Kinematic redundancy of manipulators is a well-understood topic, and various methods were developed for the redundancy resolution in order to solve the inverse kinematics problem, at least for serial manipulators. An important question, with high practical relevance, is whether the inverse kinematics solution is cyclic, i.e., whether the redundancy solution leads to a closed path in joint space as a solution of a closed path in task space. This paper investigates the cyclicity property of two widely used redundancy resolution methods, namely the projected gradient method (PGM) and the augmented Jacobian method (AJM), by means of examples. Both methods determine solutions that minimize an objective function, and from an application point of view, the sensitivity of the methods on the initial configuration is crucial. Numerical results are reported for redundant serial robotic arms and for redundant parallel kinematic manipulators. While the AJM is known to be cyclic, it turns out that also the PGM exhibits cyclicity. However, only the PGM converges to the local optimum of the objective function when starting from an initial configuration of the cyclic trajectory.

Control of a Handwriting Robot with DOF Redundancy Based on Feedback in Task Coordinates

2004 ◽  
Vol 16 (4) ◽  
pp. 381-387 ◽  
Author(s):  
Hiroe Hashiguchi ◽  
◽  
Suguru Arimoto ◽  
Ryuta Ozawa
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Sensory Feedback ◽  
Closed Loop ◽  
Joint Space ◽  
Hand Dexterity ◽  
Loop Dynamics ◽  
Additional Input ◽  
Ill Posed ◽  
Joint Motions

To enhance robot hand dexterity, it is said that the robot should be designed to have a redundant number of degrees of freedom. In redundant robotic systems, inverse kinematics from task description space to joint space becomes ill-posed, making it difficult to determine joint motions. To avoid this ill-posedness, most proposed methods introduce an additional input term calculated from an intentionally introduced artificial index of performance. We propose a 4 DOF redundant handwriting robot using novel simple control to solve the problem of ill-posedness based on sensory feedback. We demonstrate the effectiveness of proposed control in computer simulation of closed-loop dynamics with the constraint that the robot’s endpoint be always on a two-dimensional plane.

Research on Kinematics Analysis and Trajectory Planning of Novel EOD Manipulator

2021 ◽  
Vol 11 (20) ◽  
pp. 9438
Author(s):  
Jianwei Zhao ◽  
Tao Han ◽  
Xiaofei Ma ◽  
Wen Ma ◽  
Chengxiang Liu ◽  
...  
Keyword(s):  
Trajectory Planning ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Random Number ◽  
Polynomial Interpolation ◽  
Interpolation Method ◽  
Joint Space ◽  
Work Requirements ◽  
Multiple Degrees Of Freedom ◽  
Quintic Polynomial

To address the problems of mismatch, poor flexibility and low accuracy of ordinary manipulators in the complex special deflagration work process, this paper proposes a new five-degree-of-freedom (5-DOF) folding deflagration manipulator. Firstly, the overall structure of the explosion-expulsion manipulator is introduced. The redundant degrees of freedom are formed by the parallel joint axes of the shoulder joint, elbow joint and wrist pitching joint, which increase the flexibility of the mechanism. Aiming at a complex system with multiple degrees of freedom and strong coupling of the manipulator, the virtual joint is introduced, the corresponding forward kinematics model is established by D–H method, and the inverse kinematics solution of the manipulator is derived by analytical method. In the MATLAB platform, the workspace of the manipulator is analyzed by Monte Carlo pseudo-random number method. The quintic polynomial interpolation method is used to simulate the deflagration task in joint space. Finally, the actual prototype experiment is carried out using the data obtained by simulation. The trajectory planning using the quintic polynomial interpolation method can ensure the smooth movement of the manipulator and high accuracy of operation. Furthermore, the trajectory is basically consistent with the simulation trajectory, which can realize the work requirements of putting the object into the explosion-proof tank. The new 5-DOF folding deflagration manipulator designed in this paper has stable motion and strong robustness, which can be used for deflagration during the COVID-19 epidemic.

Natural Resolution of Ill-Posed Inverse Kinematics for Redundant Robots: A Challenge to Bernstein’s Degrees-of-Freedom Problem

2006 ◽  
Vol 18 (5) ◽  
pp. 651-660 ◽  
Author(s):  
Suguru Arimoto ◽  
◽  
Masahiro Sekimoto ◽  
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Sensory Feedback ◽  
Joint Space ◽  
Dimensional Manifold ◽  
Reaching Task ◽  
Loop Dynamics ◽  
Ill Posed ◽  
Human Limb ◽  
Joint Velocity

Over half a century ago, A. N. Bernstein observed that “dexterity” in human limb movement emerges from the involvement of multijoint motion with surplus degrees of freedom (DOF). Robotics posits that DOF redundancy in robot may enhance dexterity and versatility. Kinematic redundancy involves the problem of ill-posed inverse kinematics from task-description space to joint space. This problem is conventionally avoided by introducing an artificial performance index and uniquely determining an inverse kinematics solution by minimizing it. Instead of taking this conventional avoidance solution, we propose challenging Bernstein’s DOF problem by introducing two direct novel concepts - stability on a manifold and transferability to a submanifold - in dealing with human multijoint movement in reaching and showing that sensory feedback from task space to joint space together with adequate damping (joint velocity feedback) enables any solution to overall closed-loop dynamics to converge naturally and coordinately to a lower-dimensional manifold describing a set of joint states fulfilling a given motion task. This means that a reaching task is accomplished by sensory feedback with the appropriate choice of a stiffness parameter and damping coefficients without having to consider inverse kinematics. We also show that these concepts cope with the annoying “variability” of redundant joint motion seen typically in skilled human reaching. In conclusion, we propose a virtual spring/damper hypothesis that leads to natural control of skilled movement in redundant multijoint reaching.

scholarly journals A Solution of the Inverse Kinematics Problem for a 7-Degrees-of-Freedom Serial Redundant Manipulator Using Gröbner Bases Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Sérgio Ricardo Xavier da Silva ◽  
Leizer Schnitman ◽  
Vitalino Cesca Filho
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Gröbner Bases ◽  
Grobner Bases ◽  
Operational Performance ◽  
Redundant Manipulators ◽  
Redundant Manipulator ◽  
All Solutions ◽  
Inverse Kinematics Problem ◽  
Algebraic Computing

This article presents a solution of the inverse kinematics problem of 7-degrees-of-freedom serial redundant manipulators. A 7-degrees-of-freedom (7-DoF) redundant manipulator can avoid obstacles and thus improve operational performance. However, its inverse kinematics is difficult to solve since it has one more DoF than that necessary for reaching the whole workspace, which causes infinite solutions. In this article, Gröbner bases theory is proposed to solve the inverse kinematics. First, the Denavit–Hartenberg model for the manipulator is established. Second, different joint configurations are obtained using Gröbner bases theory. All solutions are confirmed with the aid of algebraic computing software, confirming that this method is accurate and easy to be implemented.

scholarly journals Voice Recognition and Inverse Kinematics Control for a Redundant Manipulator Based on a Multilayer Artificial Intelligence Network

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Mai Ngoc Anh ◽  
Duong Xuan Bien
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Voice Recognition ◽  
Learning Model ◽  
Redundant Manipulator ◽  
Efficient Operation ◽  
Inverse Kinematics Problem ◽  
Deep Learning Model

This study presents the construction of a Vietnamese voice recognition module and inverse kinematics control of a redundant manipulator by using artificial intelligence algorithms. The first deep learning model is built to recognize and convert voice information into input signals of the inverse kinematics problem of a 6-degrees-of-freedom robotic manipulator. The inverse kinematics problem is solved based on the construction and training. The second deep learning model is built using the data determined from the mathematical model of the system’s geometrical structure, the limits of joint variables, and the workspace. The deep learning models are built in the PYTHON language. The efficient operation of the built deep learning networks demonstrates the reliability of the artificial intelligence algorithms and the applicability of the Vietnamese voice recognition module for various tasks.

Another Approach for Redundancy Resolution of a 7 DOF Robotic Arm

2015 ◽  
Vol 762 ◽  
pp. 305-311
Author(s):  
Mihai Crenganis ◽  
Octavian Bologa
Keyword(s):  
Fuzzy Logic ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Robotic Arm ◽  
Cad Model ◽  
Redundancy Resolution ◽  
The Real ◽  
Kinematics Simulation ◽  
Inverse Kinematics Problem ◽  
Mathematical Equations

In this paper we have presented a method to solve the inverse kinematics problem of a redundant robotic arm with seven degrees of freedom and a human like workspace based on mathematical equations, Fuzzy Logic implementation and Simulink models. For better visualization of the kinematics simulation a CAD model that mimics the real robotic arm was created into SolidWorks® and then the CAD parts were converted into SimMechanics model.

Approach to Positioning Links of the Manipulator Using Neural Networks

2019 ◽  
Vol 20 (12) ◽  
pp. 732-739
Author(s):  
P. A. Smirnov ◽  
R. N. Yakovlev
Keyword(s):  
Neural Networks ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Linear Equations ◽  
Target Point ◽  
Positioning Systems ◽  
Solution Methods ◽  
Inverse Kinematics Problem ◽  
Manipulator Link ◽  
Robotic Devices

This paper considers development of positioning systems for manipulator links to solve the forward kinematics problem (FKP) and inverse kinematics problem (IKP). Here we study a robotic manipulator with four degrees of freedom. It should be noted, that one of the relevant research problems of modern modular robotic devices consists in the lack of the universal algorithms, that would ensure kinematics problem recalculations in the cases of reconfigurations of the whole system. Challenges, the researchers are facing with when solving this problem, have to do with geometrical and non-linear equations (trigonometric equations), finding of inverse matrix of the Denavit—Hartenberg presentation, as well with other problems, such as multiple solutions when using the analytical approach. Common mathematical solutions of the inverse kinematics problem, such as geometric, iterative and algebraic ones, may not always lead to physically appropriate solutions. It’s also noteworthy, that, trying to introduce physical solutions for the manipulator, we need to take into account, that the number of calculation formulas increases, what, in turn, causes further computing power consumption increase. If the manipulator acquires additional degrees of freedom, analytical modeling becomes virtually impossible. One of relevant inverse kinematics solution methods consists in implementation of neural networks to that end. To solve this problem various sources were analyzed, considering alternative ways of target point discovery. Considering the analyzed papers, we propose to use a perceptron. Before training the network, we compose an algorithm, calculating the Denavit—Hartman presentation matrix and check for correctness of target point reach by the terminal manipulator link. We did calculations for a thousand positions of manipulator and object in the environment, fed to the neural network. When solving FKP we obtain object coordinates as network output, whereas in the case of IKP — manipulator link angles. We present kinematic scheme testing results, as well a control scheme for a manipulator with four degrees of freedom.

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