Kinematic Calibration of Serial and Parallel Robots Based on Finite and Instantaneous Screw Theory

Sun, Tao; Lian, Binbin; Yang, Shuofei; Song, Yimin

doi:10.1109/tro.2020.2969028

Cited by 87 publications

(24 citation statements)

References 40 publications

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“…For the applications of finite screw to mechanism analysis, Huang [120][121][122] built the forward kinematic equations of some serial mechanisms. Sun and his colleagues [133][134][135][136] proposed a generic method to formulate motion equations for different types of mechanisms. Finite motion based type synthesis and instantaneous motion based kinematic analysis of parallel mechanisms are integrated by a consistent algebraic manner in their method.…”

Section: Finite Srew and Instantaneous Screwmentioning

confidence: 99%

A Survey of Mathematical Tools in Topology and Performance Integrated Modeling and Design of Robotic Mechanism

Huo

Yang

Lian

et al. 2020

Chin. J. Mech. Eng.

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Topology and performance are the two main topics dealt in the development of robotic mechanisms. However, it is still a challenge to connect them by integrating the modeling and design process of both parts in a unified frame. As the properties associated with topology and performance, finite motion and instantaneous motion of the robot play key roles in the procedure. On the purpose of providing a fundamental preparation for integrated modeling and design, this paper carries out a review on the existing unified mathematic frameworks for motion description and computation, involving matrix Lie group and Lie algebra, dual quaternion and pure dual quaternion, finite screw and instantaneous screw. Besides the application in robotics, the review of the work from these mathematicians concentrates on the description, composition and intersection operations of the finite and instantaneous motions, especially on the exponential-differential maps which connect the two sides. Furthermore, an in-depth discussion is worked out by investigating the algebraical relationship among these methods and their further progress in integrated robotic development. The presented review offers insightful investigation to the motion description and computation, and therefore would help designers to choose appropriate mathematical tool in the integrated design and modeling and design of mechanisms and robots.

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Section: Finite Srew and Instantaneous Screwmentioning

confidence: 99%

A Survey of Mathematical Tools in Topology and Performance Integrated Modeling and Design of Robotic Mechanism

Huo

Yang

Lian

et al. 2020

Chin. J. Mech. Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The product of exponentials (POE) model proposed by He et al [13] is also characterized by parameter redundancy [14]. Sun et al proposed the more concise finite and instantaneous screw (FIS) theory [15][16][17], which satisfies completeness and continuity. However, the POE and FIS models are abstract descriptions of the transformation of joint motion based on screw theory, which are convenient for calculation and programming but unintuitive and difficult to understand [14].…”

Section: Introductionmentioning

confidence: 99%

Calibration Method Based on Models and Least-Squares Support Vector Regression Enhancing Robot Position Accuracy

Bai¹,

Zhang

et al. 2021

IEEE Access

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The positioning accuracy of a robot directly affects the quality of its operations. In this study, a calibration method is proposed based on combining a model with least-squares support vector regression (LSSVR) to improve robot positioning accuracy. First, a geometric error model of the robot is established. Second, singular value decomposition (SVD) and physical model analysis method are employed to process the coupling parameters in the error model to improve the accuracy and efficiency of identification. Third, as nongeometric errors hinder the construction of an accurate and complete mathematical model and affect the residual positioning errors of the robot, LSSVR is used to compensate for the residual positioning errors caused by nongeometric errors. The proposed method thus improves the accuracy and robustness of finite sample estimation. Finally, an experiment is performed on an IRB1410 robot with a parallelogram mechanism. The maximum/mean positioning errors of the robot decrease from 2.0348/1.0978 mm to 0.1659/0.0733 mm, and the effectiveness of the proposed method is verified. The proposed method has higher prediction accuracy and stability for small samples than other methods.

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“…The main procedures for kinematic calibration include four steps: modeling, measurement, identification, and com-pensation. For modeling, the kinematic error model is established based on different mathematical tools, such as the derivative of the kinematic model [1], the product of exponential (PoE) [2], screw theory [3], bond graph theory [4], and the vector loop method [5]- [7]. In the case of the parallel robot, the vector loop method is widely utilized to establish the kinematic error model and is less complex than other methods.…”

Section: Introductionmentioning

confidence: 99%

Robot Calibration Method Based on Extended Kalman Filter–Dual Quantum Behaved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System

Cao

Nguyen

et al. 2021

IEEE Access

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This paper combines the extended Kalman filter (EKF), dual quantum-behaved particle swarm optimization (DQPSO), and adaptive neuro-fuzzy inference system (ANFIS) to propose a novel robot calibration method. Robot precision is influenced by kinematic and non-kinematic error sources. The EKF algorithm is robust for the nonlinear system with Gaussian noise to identify kinematic parameter errors for kinematic calibration. However, if inappropriate covariance matrices are selected, the EKF algorithm may converge to an incorrect solution. To increase the effectiveness of the EKF algorithm, we propose a DQPSO algorithm that consists of the QPSO-1 and QPSO-2 algorithms. The QPSO-1 algorithm adapts the covariance matrices of measurement noise and process noise, while the QPSO-2 algorithm optimizes the kinematic parameter errors estimated by the EKF algorithm. In addition, the used ANFIS predicts and compensates the non-kinematic error for non-kinematic calibration. Experiments have been performed on a five-bar parallel robot to confirm the effectiveness of the proposed method. The experimental results demonstrate that the proposed method significantly improves the positional accuracy, and is better than the previous methods. INDEX TERMSAdaptive neuro-fuzzy inference system, extended Kalman filter, dual quantum-behaved particle swarm optimization, five-bar parallel robot.

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Kinematic Calibration of Serial and Parallel Robots Based on Finite and Instantaneous Screw Theory

Cited by 87 publications

References 40 publications

A Survey of Mathematical Tools in Topology and Performance Integrated Modeling and Design of Robotic Mechanism

A Survey of Mathematical Tools in Topology and Performance Integrated Modeling and Design of Robotic Mechanism

Calibration Method Based on Models and Least-Squares Support Vector Regression Enhancing Robot Position Accuracy

Robot Calibration Method Based on Extended Kalman Filter–Dual Quantum Behaved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System

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