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Denavit–Hartenberg parameters

About: Denavit–Hartenberg parameters is a research topic. Over the lifetime, 184 publications have been published within this topic receiving 7538 citations.


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Book
01 Jan 1986
TL;DR: This chapter discusses Jacobians: Velocities and Static Forces, Robot Programming Languages and Systems, and Manipulator Dynamics, which focuses on the role of Jacobians in the control of Manipulators.
Abstract: 1. Introduction. 2. Spatial Descriptions and Transformations. 3. Manipulator Kinematics. 4. Inverse Manipulator Kinematics. 5. Jacobians: Velocities and Static Forces. 6. Manipulator Dynamics. 7. Trajectory Generation. 8. Manipulator Mechanism Design. 9. Linear Control of Manipulators. 10. Nonlinear Control of Manipulators. 11. Force Control of Manipulators. 12. Robot Programming Languages and Systems. 13. Off-Line Programming Systems.

5,992 citations

Journal ArticleDOI
TL;DR: A simple and intuitive approach to determining the kinematic parameters of a serial-link robot in Denavit-Hartenberg (DH) notation, amenable to computer algebra manipulation and a Java program is available as supplementary downloadable material.
Abstract: This paper presents a simple and intuitive approach to determining the kinematic parameters of a serial-link robot in Denavit-Hartenberg (DH) notation Once a manipulator's kinematics is parameterized in this form, a large body of standard algorithms and code implementations for kinematics, dynamics, motion planning, and simulation are available The proposed method has two parts The first is the ldquowalk through,rdquo a simple procedure that creates a string of elementary translations and rotations, from the user-defined base coordinate to the end-effector The second step is an algebraic procedure to manipulate this string into a form that can be factorized as link transforms, which can be represented in standard or modified DH notation The method allows for an arbitrary base and end-effector coordinate system as well as an arbitrary zero joint angle pose The algebraic procedure is amenable to computer algebra manipulation and a Java program is available as supplementary downloadable material

132 citations

Book
10 Dec 2011
TL;DR: In this paper, a new kinematic model, called the S-Model, is proposed for the identification of the arm signature of a robotic manipulator with rigid links, which can be used to improve the positioning accuracy of industrial robotic manipulators.
Abstract: The objective of this dissertation is to advance the state-of-the-art in the kinematic modeling, identification, and control of robotic manipulators with rigid links in an effort to improve robot kinematic performance. The positioning accuracy of commercially-available industrial robotic manipulators depends upon a kinematic model which describes the robot geometry in a parametric form. Manufacturing error in the machining and assembly of manipulators led to discrepancies between the design parameters and the physical structure. Improving the kinematic performance thus requires the identification of the actual kinematic parameters of each individual robot. The identified kinematic parameters are referred to as the arm signature. Existing robot kinematic models, such as the Denavit-Hartenberg model, are not directly applicable to kinematic parameter identification. In this dissertation we introduce a new kinematic model, called the S-Model, which is applicable to kinematic parameter identification, and use it as the foundation for our development of a general technique for identifying the kinematic parameters of any robot with rigid links. The objective of our S-Model identification algorithm is to estimate the S-Model kinematic parameters from a set of mechanical features which are inherent to the manipulator. Each revolute joint possesses two such features and each prismatic joint possesses one. These features contain the essential information to model completely the kinematics of a manipulator. The initial step of the algorithm involves the explicit identification of the feature parameters. Each feature is identified in an independent procedure and is based upon measurements of the three-dimensional Cartesian positions of target points mounted on each of the links of the manipulator. A relatively simple and systematic method for collecting these measurements is one of the practical advantages of our approach. The identified feature parameters are then used to establish the positions and orientations of Cartesian coordinate frames fixed relative to each link of the manipulator in accordance with the definition of the S-Model. The parameters of the S-Model are then computed from the estimated link coordinate frame locations. Finally, the Denavit-Hartenberg parameters for the manipulator are extracted from the identified S-Model parameters. We have implemented a complete prototype arm signature identification system and have applied it to identify the signatures and control the end-effector of seven Unimation/Westinghouse Puma 560 robots. Evaluation of the experimental results has demonstrated consistent and significant improvements in the kinematic performance of all the robots tested.

128 citations

Journal ArticleDOI
TL;DR: This paper aims to integrate didactically some engineering concepts to understand and teach the screw- based methods applied to the kinematic modeling of robot manipulators, including a comparative analysis between these and the Denavit-Hartenberg-based methods.
Abstract: This paper aims to integrate didactically some engineering concepts to understand and teach the screw-based methods applied to the kinematic modeling of robot manipulators, including a comparative analysis between these and the Denavit-Hartenberg-based methods. In robot analysis, kinematics is a fundamental concept to understand, since most robotic mechanisms are essentially designed for motion. The kinematic modeling of a robot manipulator describes the relationship between the links and joints that compose its kinematic chain. To do so, the most popular methods use the Denavit-Hartenberg convention or its variations, presented by several author and robot publications. This uses a minimal parameter representation of the kinematic chain, but has some limitations. The successive screw displacements method is an alternative representation to this classic approach. Although it uses a non-minimal parameter representation, this screw-based method has some advantages over Denavit-Hartenberg. Both methods are here presented and compared, concerning direct/inverse kinematics of manipulators. The differential kinematics is also discussed. Examples of kinematic modeling using both methods are presented in order to ease their comparison.

121 citations

Journal ArticleDOI
TL;DR: This stochastic analysis of anatomical variability redefines the debate on whether a single generic biomechanical model can represent the entire population, or if subject-specific models are necessary, and suggests a practical third alternative: that anatomical and functional variability can be captured by a finite set of model-types.
Abstract: A realistic biomechanical thumb model would elucidate the functional consequences of orthopedic and neurological diseases and their treatments. We investigated whether a single parametric kinematic model can represent all thumbs, or whether different kinematic model structures are needed to represent different thumbs. We used Monte Carlo simulations to convert the anatomical variability in the kinematic model parameters into distributions of Denavit-Hartenberg parameters amenable for robotics-based models. Upon convergence (3550 simulations, where mean and coefficient of variance changed <1% for the last 20+% simulations) the distributions of Denavit-Hartenberg parameters appeared multimodal, in contrast to the reported unimodal distributions of the anatomy-based parameters. Cluster analysis and one-way analysis of variance confirmed four types of kinematic models (p<0.0001) differentiated primarily by the biomechanically relevant order of MCP joint axes (in 65.2% of models, the flexion-extension axis was distal to the adduction-abduction axis); and secondarily by a detail specifying the direction of a common normal between successive axes of rotation. Importantly, this stochastic analysis of anatomical variability redefines the debate on whether a single generic biomechanical model can represent the entire population, or if subject-specific models are necessary. We suggest a practical third alternative: that anatomical and functional variability can be captured by a finite set of model-types.

102 citations

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20221
202110
202018
201919
201817
201711