A systematic approach to identify the error motion of anN-degree of freedom manipulator

Harb, S.; Burdekin, M.

doi:10.1007/bf01750419

Cited by 11 publications

(3 citation statements)

References 19 publications

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“…Most of the authors considered the main source of errors to be only geometric, with the exception of (Chen at al., 1987) and Whitney et al (Whitney et al, 1986), who included explicitly non-geometric errors as well. Although some introduced their own models (Whitney et al, 1986), the majority used models that are universally valid and widely accepted, such as the Denavit-Hartenberg or modified versions of it ((Khalil et al, 1991), (Driels, 1993) and (Harb & Burdekin, 1994)). Much previous work is based only on computer simulations, but some validation work used real measurements ( (Chen at al., 1987), (Whitney et al, 1986), (Stone, 1987) (Stanton & Parker, 1992) (Khalil et al, 1991), (Driels, 1993), (Driels & Pathre, 1994) and (Abderrahim & Whittaker, 2000)), and very recently there is even commercial application dedicated to robot calibration ((Renders, 2006) and (Fixel, 2006)).…”

Section: Calibration Overviewmentioning

confidence: 99%

Accuracy and Calibration Issues of Industrial Manipulators

Abderrahim¹,

Khamis²,

Garrido³

et al. 2006

Industrial Robotics: Programming, Simulation and Applications

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Section: Calibration Overviewmentioning

confidence: 99%

Accuracy and Calibration Issues of Industrial Manipulators

Abderrahim¹,

Khamis²,

Garrido³

et al. 2006

Industrial Robotics: Programming, Simulation and Applications

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“…Recent research also shows a focus on invasive, contact techniques intended mainly for calibration. Harb and Burdekin [21] described a generalized calibration technique to extract the Denavit -Hartenberg parameters, and non-geometric errors such as backlash and gear transmission error were also identified with axis-by-axis measurements. Juneja and Goldenberg propose an artefact-based calibration [22], while Roning and Korzun [23] propose a measure of trajectory error, with the advantage that the technique can be performed in the workplace.…”

Section: Research In Performance Criteria Monitoringmentioning

confidence: 99%

Failure analysis of mature robots in automated production

Starr

Wynne

Kennedy

1999

Proceedings of the Institution of Mechanical Engineers, Part B:

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Robot failures are costly and difficult to diagnose. Breakdown data for robot-automated production lines, collected from automotive applications, showed that nearly half of robot failures are caused by positional error. A further quarter were attributed to drive failures. Positional error may be caused by a number of mechanical failure modes or by poor tuning of the control system. Testing of repeatability or absolute position in the work place is hard because the robot moves quickly, allowing little time for measurement. Measurement may be required in up to six axes. The end-effectors of a robot, e.g. welding guns, grinding wheels and sealant applicators, are powerful and unguarded, and are not compatible with conventional contact, or close proximity non-contact, transducers.This paper presents significant new industrial evidence of the need for advanced diagnostic techniques in industrial robotics. Historical records for about 200 robots in automotive applications were analysed, identifying the major failure modes. Existing maintenance and condition monitoring methods were audited, and the problems of selecting condition monitoring methods for robots were analysed, identifying characteristics that differ from application in calibration. Measurement methods are briefly reviewed in the paper. It is concluded that non-invasive, non-contact methods are a prerequisite for operational effectiveness.

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“…On the one hand, robotics need to reach thousands of point in a wide range of space, on the other hand these scenarios involve complicated curves and surfaces, so CAD software combined with robot off-line programming has become the mainstream method. Danevit and Hartenberg [1] proposed the best-known DH parameter method, which used differential kinematics to establish the identification Jacobian matrix and mapped the end error to various geometric parameters [2]. Due to the weak rigidity of motor gears and reducer at robot joints, the position accuracy decreases obviously under the heavy payloads or high speed motion, so the modeling of robot stiffness is also one of the focuses of research.…”

Section: Introductionmentioning

confidence: 99%

Compensation Methods for Industrial Robotics Under Varying Payloads with Deep Reinforcement Learning

Xiao

Sun

2022

Advances in Transdisciplinary Engineering

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Due to the weak rigidity of an industrial robot, its end effector usually has poor absolute positioning accuracy, especially under varying payloads. Such situation is common in scenarios of handling, machining and tool changing. Conventional off-line calibration or compensation methods can only eliminate systematic errors, while such methods are invalid to the dynamic errors brought by varying payloads. This paper proposes a deep reinforcement learning(DRL) approach to solve the problem of dynamic errors, in consideration of external payloads changed manually. An online full closed loop system is established to verify the proposed method, which consists of a KUKA robot KR6, a Leica laser tracker, and a BECKHOFF PLC controller. The robot and the laser tracker work as the slavers of the master PLC controller, in between the communication is accomplished using EtherCAT. Logically, the robot is controlled by mxAutomation and the laser tracker is connected to an embedded EtherCAT slave card. Experiments on the robot demonstrate the effectiveness of the proposed DRL methods. The changed payloads range from 1.177Kg to 4.179 Kg, while the position accuracy of the robot can be maintained no more than 0.4mm by the DRL algorithm.

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A systematic approach to identify the error motion of anN-degree of freedom manipulator

Abstract: A generalised calibration technique for identifying the joint geometric parameters of an N-degrees-of-freedom ( d. o.f. )

Cited by 11 publications

References 19 publications

Accuracy and Calibration Issues of Industrial Manipulators

Accuracy and Calibration Issues of Industrial Manipulators

Failure analysis of mature robots in automated production

Compensation Methods for Industrial Robotics Under Varying Payloads with Deep Reinforcement Learning

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