Measurement of unidirectional pose accuracy and repeatability of the collaborative robot UR5

Pollák, Martin; Kočiško, Marek; Paulišin, Dušan; Baron, Petr

doi:10.1177/1687814020972893

Cited by 27 publications

(10 citation statements)

References 14 publications

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“…Therefore, kinematic modeling is established based on the basic parameters of each link and the essential parameters of the mobile platform. However, many shortcomings have been observed in the kinematic modeling results of the mobile manipulator robot based on other studies [41,42].…”

Section: Limitations Of Kinematic Modelingmentioning

confidence: 99%

“…In this article, the initial parameters and installation positions of these motors are similar to the typical UR5 robot. To simplify the control of the UR arm, researchers have developed a classical kinematic modeling result based on the Standard Denavit-Hartenberg (SDH) method [41]. Therefore, the kinematic modeling of the manipulator subsystem based on the classical method is shown in Figure 2a.…”

Section: Limitations Of Kinematic Modeling Of the Manipulatormentioning

confidence: 99%

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Optimizing Kinematic Modeling and Self-Collision Detection of a Mobile Manipulator Robot by Considering the Actual Physical Structure

Qiao

Luo

et al. 2021

Applied Sciences

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In this paper, an optimized kinematic modeling method to accurately describe the actual structure of a mobile manipulator robot with a manipulator similar to the universal robot (UR5) is developed, and an improved self-collision detection technology realized for improving the description accuracy of each component and reducing the time required for approximating the whole robot is introduced. As the primary foundation for trajectory tracking and automatic navigation, the kinematic modeling technology of the mobile manipulator has been the subject of much interest and research for many years. However, the kinematic model established by various methods is different from the actual physical model due to the fact that researchers have mainly focused on the relationship between driving joints and the end positions while ignoring the physical structure. To improve the accuracy of the kinematic model, we present a kinematic modeling method with the addition of key points and coordinate systems to some components that failed to model the physical structure based on the classical method. Moreover, self-collision detection is also a primary problem for successfully completing the specified task of the mobile manipulator. In traditional self-collision detection technology, the description of each approximation is determined by the spatial transformation of each corresponding component in the mobile manipulator robot. Unlike the traditional technology, each approximation in the paper is directly established by the physical structure used in the kinematic modeling method, which significantly reduces the complicated analysis and shortens the required time. The numerical simulations prove that the kinematic model with the addition of key point technology is similar to the actual structure of mobile manipulator robots, and the self-collision detection technology proposed in the article effectively improves the performance of self-collision detection. Additionally, the experimental results prove that the kinematic modeling method and self-collision detection technology outlined in this paper can optimize the inverse kinematics solution.

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Section: Limitations Of Kinematic Modelingmentioning

confidence: 99%

Section: Limitations Of Kinematic Modeling Of the Manipulatormentioning

confidence: 99%

Optimizing Kinematic Modeling and Self-Collision Detection of a Mobile Manipulator Robot by Considering the Actual Physical Structure

Qiao

Luo

et al. 2021

Applied Sciences

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“…These tasks often involve robot end-effector manipulation operations, where manipulation of the robot end-effector to accurately attain desired positions and configurations is paramount. To proficiently execute multiple manipulation tasks, it is important for robot positioning to not only be repeatable but also accurate [3][4][5] . However, achieving high-accuracy robotic positioning remains a challenge, which needs to be addressed to expand the industrial use of robots.…”

Section: Introductionmentioning

confidence: 99%

High-accuracy robotic metrology for precise industrial manipulation tasks

Isa,

Khanesar,

Leach

et al. 2023

Automated Visual Inspection and Machine Vision V

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The majority of industrial production processes can be divided into a series of object manipulation and handling tasks that can be adapted for robots. Through significant advances in compliant grasping, sensing and actuation technologies, robots are now capable of carrying out human-like flexible and dexterous object manipulation tasks. During operation, robots are required to position objects within tolerances specified for every operation in an industrial process. The ability of a robot to meet these tolerances is the critical deciding factor that determines where the robot can be integrated and how proficient the robot can carry out high-precision tasks. Therefore, improving the positioning accuracy of robots can lead to new avenues for their integration into production industries. Given that tolerances in manufacturing processes are in the order of tens of micrometres or less, robots should guarantee high positioning accuracy when manipulating objects. The direct method of ensuring high accuracy is by introducing an additional measurement system(s) that can improve the inherent joint-angle-based robot position determination. In this paper, we present a high-accuracy robotic pose measurement (HARPM) system based on coordinate measurements from a multi-camera vision system. We also discuss the integration of measurements obtained by absolute distance interferometry and how the interferometric measurements can complement the vision system measurements. The performance of the HARPM system is evaluated using a laser interferometer to investigate robotic positions along a trajectory. The performance results show that the HARPM system can improve the positioning accuracy of robots from hundreds to a few tens of micrometres.

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“…By evaluating results of pose repeatability, it can be said that the repeatability of the robot at the selected area of its workspace corresponds to the repeatability value stated by the manufacturer (±0.02 mm). Pollak [15] describes the measurement of unidirectional pose accuracy and repeatability of a collaborative robot. e objective of the measurements is to investigate and evaluate unidirectional accuracy of the six-axis collaborative robot UR5 of the company Universal Robots.…”

Section: Introductionmentioning

confidence: 99%

A Point Cloud-Based Feature Recognition and Path Planning Method

Chen

Wang

Huang

2022

Shock and Vibration

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Based on the research background of in situ automatic ultrasonic phased array inspection of irregular porous castings, due to the limited in situ inspection stations, complex shape of irregular porous castings, and extreme multireflection structural features, it is necessary to identify the positioning inspection features among multiple features to be inspected and plan the optimal inspection path. This research is interested in the porous location recognition and its detection path planning of irregular porous castings. For this, a point cloud-based multifeature contour recognition and location algorithm were proposed to simultaneously extract and locate the hole feature and cylindrical feature from an irregular porous castings. Furthermore, a detection path planning method was put forward to search the shortest robot’s detection path based on the above acquired features by visual recognition and positioning technology. First, through the calibration of the industrial robot tool coordinate system and the internal and external parameters of the camera, the “EyeinHand” hand-eye conversion relationship was established. Second, the robot vision system collects the point cloud information of the area to be inspected and performs point cloud splicing, the accuracy of the original data, the removal of noise such as invalid points, outliers and internal noise points, on this basis, the boundary curve of the hole to be inspected was extracted, the cylindrical equation was fitted, its geometric center was calculated, and the central coordinates and axis direction of the contour of the hole to be inspected were obtained. Finally, all the detection paths were traversed through the multibranch tree to obtain the optimal detection path of the detection points of multiple targets. The experimental results show that the positioning accuracy of the feature of the hole to be inspected by the vision system is 0.107 mm, the aperture extraction accuracy is 0.002 mm, the cylinder fitting accuracy is 0.04 mm, and the calculation accuracy of the angle between the two axes is within 0.4. When the number of features to be inspected is different, the average moving distance can be saved by 10.7% by using the end effector after path optimization. The feasibility of in situ automatic ultrasonic phased array detection for irregular porous castings using by visual positioning is verified.

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Measurement of unidirectional pose accuracy and repeatability of the collaborative robot UR5

Cited by 27 publications

References 14 publications

Optimizing Kinematic Modeling and Self-Collision Detection of a Mobile Manipulator Robot by Considering the Actual Physical Structure

Optimizing Kinematic Modeling and Self-Collision Detection of a Mobile Manipulator Robot by Considering the Actual Physical Structure

High-accuracy robotic metrology for precise industrial manipulation tasks

A Point Cloud-Based Feature Recognition and Path Planning Method

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