Inverse Kinematics Analysis of 7-DOF Collaborative Robot by Decoupling Position and Orientation

2021 ◽  
pp. 217-227
Author(s):  
Nguyen Quang Hoang ◽  
Do Tran Thang ◽  
Dinh Van Phong
Keyword(s):  
Inverse Kinematics ◽  
Kinematics Analysis ◽  
Position And Orientation ◽  
Collaborative Robot

Inverse Kinematics and Dynamics of a 3-DOF Spatial Parallel Manipulator

2012 ◽  
Vol 229-231 ◽  
pp. 2280-2284
Author(s):  
Jian Xin Yang ◽  
Ben Zhao ◽  
Chun Li Li
Keyword(s):  
Inverse Kinematics ◽  
Parallel Manipulator ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Rotational Degree ◽  
Kinematics Analysis ◽  
Inverse Dynamic ◽  
Generalized Coordinates ◽  
Euler Approach ◽  
Position And Orientation

Recently the parallel manipulator with less DOFs has attracted industry and academia, but the research on its dynamics is still an open problem. In this paper, the inverse dynamic of a spatial parallel manipulator with two translational degrees of freedom and one rotational degree of freedom is studied based on the Newton-Euler approach. The kinematics analysis is firstly performed in a closed form. The inverse dynamic equation of this manipulator is formulated by using the Lagrange multiplier approach and choosing the Cartesian position and orientation as the generalized coordinates. Finally a numerical example is given for the kinematic and dynamic simulation of this manipulator. The model will be useful to improve the design of the mechanical components and the control algorithm.

scholarly journals Kinematics Analysis of 5 DOF Robotic Arm

2020 ◽  
Vol 38 (3A) ◽  
pp. 412-422
Author(s):  
Tahseen F. Abaas ◽  
Ali A. Khleif ◽  
Mohanad Q. Abbood
Keyword(s):  
Inverse Kinematics ◽  
Jacobian Matrix ◽  
Maximum Error ◽  
Robotic Arm ◽  
Forward Kinematics ◽  
Algebraic Solution ◽  
Kinematics Analysis ◽  
End Effector ◽  
Position And Orientation

This paper presents the forward, inverse, and velocity kinematics analysis of a 5 DOF robotic arm. The Denavit-Hartenberg (DH) parameters are used to determination of the forward kinematics while an algebraic solution is used in the inverse kinematics solution to determine the position and orientation of the end effector. Jacobian matrix is used to calculate the velocity kinematics of the robotic arm. The movement of the robotic arm is accomplished using the microcontroller (Arduino Mega2560), which controlling on five servomotors of the robotic arm joints and one servo of the gripper. The position and orientation of the end effector are calculated using MATLAB software depending on the DH parameters. The results indicated the shoulder joint is more effect on the velocity of the robotic arm from the other joints, and the maximum error in the position of the end-effector occurred with the z-axis and minimum error with the y-axis.

scholarly journals Kinematics Analysis of a Novel Five-Degree-of-Freedom Spatial Parallel Micromanipulator

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Daniel Prusak ◽  
Konrad Kobus ◽  
Grzegorz Karpiel
Keyword(s):  
Mathematical Model ◽  
Piezoelectric Actuator ◽  
Analytical Solutions ◽  
Inverse Kinematics ◽  
Geometrical Model ◽  
Degree Of Freedom ◽  
Kinematics Analysis ◽  
Moving Platform ◽  
Position And Orientation ◽  
The Mathematical Model

A study of the inverse kinematics for a five-degree-of-freedom (DOF) spatial parallel micromanipulator is presented here below. The objective of this paper is the introduction of a structural and geometrical model of a novel five-degree-of-freedom spatial parallel micromanipulator, analysis of the effective and useful workspace of the micromechanism, presentation of the obtained analytical solutions of the microrobot’s inverse kinematics tasks, and verification of its correctness using selected computer programs and computation environments. The mathematical model presented in this paper describes the behaviour of individual elements for the applied 2-DOF novel piezoelectric actuator, resulting from the position and orientation of the microrobot’s moving platform.

scholarly journals CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots

2021 ◽  
Vol 11 (9) ◽  
pp. 4269
Author(s):  
Kamil Židek ◽  
Ján Piteľ ◽  
Michal Balog ◽  
Alexander Hošovský ◽  
Vratislav Hladký ◽  
...  
Keyword(s):  
Mixed Reality ◽  
Current Trend ◽  
Robot Vision ◽  
Processing Unit ◽  
Single Shot ◽  
Vision Systems ◽  
Collaborative Robots ◽  
Training Time ◽  
Position And Orientation ◽  
Collaborative Robot

The assisted assembly of customized products supported by collaborative robots combined with mixed reality devices is the current trend in the Industry 4.0 concept. This article introduces an experimental work cell with the implementation of the assisted assembly process for customized cam switches as a case study. The research is aimed to design a methodology for this complex task with full digitalization and transformation data to digital twin models from all vision systems. Recognition of position and orientation of assembled parts during manual assembly are marked and checked by convolutional neural network (CNN) model. Training of CNN was based on a new approach using virtual training samples with single shot detection and instance segmentation. The trained CNN model was transferred to an embedded artificial processing unit with a high-resolution camera sensor. The embedded device redistributes data with parts detected position and orientation into mixed reality devices and collaborative robot. This approach to assisted assembly using mixed reality, collaborative robot, vision systems, and CNN models can significantly decrease assembly and training time in real production.

A Model of the Human Spine: Forward and Inverse Kinematics

1992 ◽  
Author(s):  
Sunil Kumar Agrawal ◽  
Siyan Li ◽  
Glen Desmier
Keyword(s):  
Range Of Motion ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Kinematic Model ◽  
Joint Angles ◽  
Human Spine ◽  
Forward And Inverse Kinematics ◽  
Position And Orientation ◽  
Three Degrees Of Freedom ◽  
Adjacent Vertebra

Abstract The human spine is a sophisticated mechanism consisting of 24 vertebrae which are arranged in a series-chain between the pelvis and the skull. By careful articulation of these vertebrae, a human being achieves fine motion of the skull. The spine can be modeled as a series-chain with 24 rigid links, the vertebrae, where each vertebra has three degrees-of-freedom relative to an adjacent vertebra. From the studies in the literature, the vertebral geometry and the range of motion between adjacent vertebrae are well-known. The objectives of this paper are to present a kinematic model of the spine using the available data in the literature and an algorithm to compute the inter vertebral joint angles given the position and orientation of the skull. This algorithm is based on the observation that the backbone can be described analytically by a space curve which is used to find the joint solutions..

Parametric Design of a Spherical Eight-Bar Linkage Based on a Spherical Parallel Manipulator

2008 ◽  
Vol 1 (1) ◽  
Author(s):  
Gim Song Soh ◽  
J. Michael McCarthy
Keyword(s):  
Inverse Kinematics ◽  
Parallel Manipulator ◽  
Parametric Design ◽  
Degree Of Freedom ◽  
Kinematics Analysis ◽  
End Effector ◽  
Arbitrary Base ◽  
Three Degree Of Freedom ◽  
Spherical Parallel Manipulator

This paper presents a procedure that determines the dimensions of two constraining links to be added to a three degree-of-freedom spherical parallel manipulator so that it becomes a one degree-of-freedom spherical (8, 10) eight-bar linkage that guides its end-effector through five task poses. The dimensions of the spherical parallel manipulator are unconstrained, which provides the freedom to specify arbitrary base attachment points as well as the opportunity to shape the overall movement of the linkage. Inverse kinematics analysis of the spherical parallel manipulator provides a set of relative poses between all of the links, which are used to formulate the synthesis equations for spherical RR chains connecting any two of these links. The analysis of the resulting spherical eight-bar linkage verifies the movement of the system.

scholarly journals IKBT: Solving Symbolic Inverse Kinematics with Behavior Tree (Extended Abstract)

2020 ◽  
Author(s):  
Dianmu Zhang ◽  
Blake Hannaford
Keyword(s):  
Closed Form ◽  
Inverse Kinematics ◽  
Intelligent System ◽  
Logical Reasoning ◽  
Robot Arm ◽  
Kinematics Analysis ◽  
Closed Form Solutions ◽  
Behavior Tree ◽  
Behavior Trees ◽  
High Level

Inverse kinematics solves the problem of how to control robot arm joints to achieve desired end effector positions, which is critical to any robot arm design and implementations of control algorithms. It is a common misunderstanding that closed-form inverse kinematics analysis is solved. Popular software and algorithms, such as gradient descent or any multi-variant equations solving algorithm, claims solving inverse kinematics but only on the numerical level. While the numerical inverse kinematics solutions are relatively straightforward to obtain, these methods often fail, even when the inverse kinematics solutions exist. Therefore, closed-form inverse kinematics analysis is superior, but there is no generalized automated algorithm. Up till now, the high-level logical reasoning involved in solving closed-form inverse kinematics made it hard to automate, so it's handled by human experts. We developed IKBT, a knowledge-based intelligent system that can mimic human experts' behaviors in solving closed-from inverse kinematics using Behavior Tree. Knowledge and rules used by engineers when solving closed-from inverse kinematics are encoded as actions in Behavior Tree. The order of applying these rules is governed by higher level composite nodes, which resembles the logical reasoning process of engineers. It is also the first time that the dependency of joint variables, an important issue in inverse kinematics analysis, is automatically tracked in graph form. Besides generating closed-form solutions, IKBT also explains its solving strategies in human (engineers) interpretable form. This is a proof-of-concept of using Behavior Trees to solve high-cognitive problems.

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