A methodology for industrial robot calibration based on measurement sub-regions

Toquica, Juan S.; Motta, José Maurício Santos Torres da

doi:10.1007/s00170-021-08308-4

Cited by 13 publications

(6 citation statements)

References 45 publications

(6 reference statements)

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“…Then, the laser tracker is used to measure 7000 points in a spatial array as reference data, as shown in Figure 13 . Following the layout design in references [ 32 , 33 ], these 7000 points are arranged in seven robot orientations, with each pose set up in a 10³ configuration. The final distribution of the measurement points across the six joint spaces of the robot is depicted in Figure 14 , with the least active joint reaching an approximate range of 50°.…”

Section: Calibration Experiments Of Kinematic and Joint Compliance Modelmentioning

confidence: 99%

Kinematic and Joint Compliance Modeling Method to Improve Position Accuracy of a Robotic Vision System

Ye,

Jia,

Wang

et al. 2024

Sensors

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In the field of robotic automation, achieving high position accuracy in robotic vision systems (RVSs) is a pivotal challenge that directly impacts the efficiency and effectiveness of industrial applications. This study introduces a comprehensive modeling approach that integrates kinematic and joint compliance factors to significantly enhance the position accuracy of a system. In the first place, we develop a unified kinematic model that effectively reduces the complexity and error accumulation associated with the calibration of robotic systems. At the heart of our approach is the formulation of a joint compliance model that meticulously accounts for the intricacies of the joint connector, the external load, and the self-weight of robotic links. By employing a novel 3D rotary laser sensor for precise error measurement and model calibration, our method offers a streamlined and efficient solution for the accurate integration of vision systems into robotic operations. The efficacy of our proposed models is validated through experiments conducted on a FANUC LR Mate 200iD robot, showcasing notable improvements in the position accuracy of robotic vision system. Our findings contribute a framework for the calibration and error compensation of RVS, holding significant potential for advancements in automated tasks requiring high precision.

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Section: Calibration Experiments Of Kinematic and Joint Compliance Modelmentioning

confidence: 99%

Kinematic and Joint Compliance Modeling Method to Improve Position Accuracy of a Robotic Vision System

Ye,

Jia,

Wang

et al. 2024

Sensors

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“…Its joint limits allow ample functional workspace duty, as summarized in Table I [51]. The robotic manipulator includes an IRC5 controller [52][53], a multi-robot controller with PC tool support that optimises robot performance for short cycle times and precise movements, and RobotWare (Robot Studio), which allows ABB robot programming on a workstation without shutting down production [54] [55]. A program can be built on the ABB Virtual Controller, which is an exact copy of the software that runs robots in production.…”

Section: IImentioning

confidence: 99%

The Impact of Simplifications of the Dynamic Model on the Motion of a Six-Jointed Industrial Articulated Robotic Arm Movement

Fazilat,

Zioui

2024

Journal of Robotics and Control

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This research investigates the impact of model simplification on the dynamic performance of an ABB IRB-140 six-jointed industrial robotic arm, concentrating on torque prediction and energy consumption. The entire mathematical model of forward, reverse, differential kinematics, and dynamic model proposed based on the technical specifications of the arm, and to obtain the center of the mass and inertia matrices, which are essential components of the dynamic model, Utilizing Solidworks, we developed three CAD/CAM models representing the manipulator with varying detail levels, such as simplified, semi-detailed, and detailed. Our findings indicate minor differences in the model's torque and energy consumption graphs. The semi-detailed model consumed the most energy, except for joint 1, with the detailed model showing a 0.53% reduction and the simplified model a 6.8% reduction in energy consumption. Despite these variations, all models proved effective in predicting the robot's performance during a standard 30-second task, demonstrating their adequacy for various industrial applications. This research highlights the balance between computational efficiency and accuracy in model selection. While the detailed model offers the highest precision, it demands more computational resources, which is suitable for high-precision tasks. In discrepancy, simplified, less precise models offer computational efficiency, making them adequate for specific scenarios. Our study provides critical insights into selecting dynamic models in industrial robotics. It guides the optimization of performance and energy efficiency based on the required task precision and available computational resources. This comprehensive comparison of dynamic models underscores their applicability and effectiveness in diverse industrial settings.

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“…Industrial robots are crucial automation assets in modern manufacturing, integrating advanced technologies from diverse fields such as mechanical engineering, electronics, control systems, computing, sensors, and artificial intelligence. Their applications span a wide spectrum, encompassing welding, painting, assembling, packaging, and undersea operations [1][2][3][4]. Heavy-duty industrial robots, distinguished by their flexibility, high payload capacity, and cost-effectiveness, are particularly adept at handling large and heavy workpieces, showcasing remarkable advantages in heavy industries.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Characterization and Incremental Dynamics Calibration of the Heavy-Duty Industrial Robot: A Focus on Hydraulic Equilibrium Dynamics

Cheng,

Xu,

Liang

et al. 2024

Preprint

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In recent decades, industrial robots have emerged as pivotal contributors to the global manufacturing landscape, revolutionizing various sectors through increased automation and efficiency. Simultaneously, the application of heavy-duty robots in heavy industries is gradually increasing. In this study, a self-developed heavy-duty robot is utilized for automated fiber placement (AFP), with the layup equipment integrated at the robot's end effector, weighing over one ton. To ensure the precision and efficiency of AFP, particular attention is given to the dynamic performance of the robot. The heavy-duty robot is equipped with a hydraulic equilibrium system to alleviate the gravitational load on the joint motors of both the robot body and the end effector. The hydraulic equilibrium system consists of a bladder accumulator and a hydraulic cylinder, introducing complexity to the robot dynamics. Therefore, establishing a dynamic model of the robot system and obtaining accurate dynamic parameters serve as the foundation for precise control of the robot, enabling the full utilization of its dynamic capabilities. In this paper, dynamics modeling of the hydraulic equilibrium system is performed based on the Maxwell model, and its dynamic parameters are identified using the CARAM model. Subsequently, the multi-body dynamic model of the robot is established, and an incremental identification algorithm for dynamic parameters is devised based on the characteristics of the robot structure. Additionally, to accurately identify dynamic parameters, an analysis of the robot drive mechanism is conducted to obtain the equivalent reduction ratio of the joints and the lever arm of the hydraulic equilibrium system. Furthermore, an equivalent friction model for the robot joints and screws is established.

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A methodology for industrial robot calibration based on measurement sub-regions

Cited by 13 publications

References 45 publications

Kinematic and Joint Compliance Modeling Method to Improve Position Accuracy of a Robotic Vision System

Kinematic and Joint Compliance Modeling Method to Improve Position Accuracy of a Robotic Vision System

The Impact of Simplifications of the Dynamic Model on the Motion of a Six-Jointed Industrial Articulated Robotic Arm Movement

Dynamic Characterization and Incremental Dynamics Calibration of the Heavy-Duty Industrial Robot: A Focus on Hydraulic Equilibrium Dynamics

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