A Mobile Robotic 3-D Measurement Method Based on Point Clouds Alignment for Large-Scale Complex Surfaces

Wang, Jinshan; Tao, Bo; Gong, Zeyu; Yu, Wenfu; Yin, Zhouping

doi:10.1109/tim.2021.3090156

Cited by 30 publications

(18 citation statements)

References 29 publications

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“…equation (1). Due to the limitations of the rectangle metric and in order to reduce the false-positive grasps, we will improve the standard, that is, increase the Jaccard threshold to 0.30, 0.35, and 0.4 and reduce the angle difference between predicted and ground truth, and then test the performance on two public datasets.…”

Section: B Implementation Detailsmentioning

confidence: 99%

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A Novel Generative Convolutional Neural Network for Robot Grasp Detection on Gaussian Guidance

Li¹,

Liu²,

Ma³

et al. 2022

Preprint

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The vision-based grasp detection method is an important research direction in the field of robotics. However, due to the rectangle metric of the grasp detection rectangle's limitation, a false-positive grasp occurs, resulting in the failure of the real-world robot grasp task. In this paper, we propose a novel generative convolutional neural network model to improve the accuracy and robustness of robot grasp detection in realworld scenes. First, a Gaussian-based guided training method is used to encode the quality of the grasp point and grasp angle in the grasp pose, highlighting the highest-quality grasp point position and grasp angle and reducing the generation of falsepositive grasps. Simultaneously, deformable convolution is used to obtain the shape features of the object in order to guide the subsequent network to the position. Furthermore, a global-local feature fusion method is introduced in order to efficiently obtain finer features during the feature reconstruction stage, allowing the network to focus on the features of the grasped objects. On the Cornell Grasping Datasets and Jacquard Datasets, our method achieves excellent performance of 99.0% and 95.9%, respectively. Finally, the proposed method is put to the test in a real-world robot grasping scenario.

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Section: B Implementation Detailsmentioning

confidence: 99%

“…W ITH the development of information technology and control technology, robots are becoming more important in industrial manufacturing [1], medical assistance [2], social service [3], and space exploration [4]. Grasping objects is the most widely used robot task and one of the most challenging technologies in robot operation.…”

Section: Introductionmentioning

confidence: 99%

A Novel Generative Convolutional Neural Network for Robot Grasp Detection on Gaussian Guidance

Li¹,

Liu²,

Ma³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…It is embodied in that the individual’s personality, intelligence, age, and gender will indirectly affect the behavioral intention and behavior ( Klaus and Zaichkowsky, 2022 ). Moreover, in the technology acceptance model, it is also pointed out that perceived convenience will also be affected by individual characteristics ( Wang et al, 2021 ). Therefore, consumer characteristics are set as control variables to consider their impact on other variables.…”

Section: Theoretical Basis and Research Hypothesismentioning

confidence: 99%

The Promotion and Optimization of Bank Financial Products Using Consumers’ Psychological Perception

Zhang

Jin

2022

Front. Psychol.

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With the rapid economic growth and increased national income year by year, individuals and families have an increasingly greater demand for financial products. Banks’ sales of financial products have become a new economic profit growth point for major banks. Based on consumers’ psychological perception, the influencing factors of consumers’ behavior in purchasing bank financial products are studied. The influencing factor model path of consumer purchase behavior is constructed to find out the factors affecting consumers’ purchase of bank financial products and formulate appropriate promotion strategies according to the influencing factors. Through the research methods of literature analysis, small-scale in-depth interview, questionnaire surveys, and statistical analysis, this exploration selects four variables: independent variable, mediator, control variable, and dependent variable. They are influencing factors of purchasing bank financial products (perceived convenience, risk value of bank financial products, satisfaction of purchasing communication process), consumers’ willingness to buy bank financial products, consumers’ personal characteristics and consumers’ behavior of purchasing bank financial products. Meanwhile, based on 196 valid questionnaires, regression analysis is carried out through a regression model. The results show that the three influencing factors of consumers’ purchase of bank financial products–perceived convenience, risk value of bank financial products, and satisfaction with the purchase communication process significantly impact consumers’ purchase of bank financial products. They can put forward specific promotion suggestions for banks. This exploration aims to study the optimization of bank financial product promotion strategy from the perspective of consumer psychological perception to provide a reference for subsequent related research.

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“…In this regard, the team led by Tao Bo came up with a mobile robotic measurement system for large-scale complex components based on optical scanning and visual tracking, achieving the positioning of the robot by measuring scanner and coded marks on the ground. In the actual measurement of a 2.88 m wind turbine blade model, the translation error is less than 0.2 mm [29,30]. Although the measurement accuracy is very high, the ground coding and marking process also increases the complexity of the measurement task.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Measurement System of Dual Mobile Robots That Integrates Visual Tracking and 3D Measurement

Gan

Ren

et al. 2022

Machines

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The manufacturing accuracy of large-scale complex components determines the performance and quality of aircraft, ships, high-speed rail, and other equipment. High-precision 3D measurement plays a crucial role in ensuring manufacturing accuracy. At present, the existing measurement methods rely heavily on manual labor, which cannot satisfy the requirements of industry quality and efficiency. This paper introduces an integrated mobile robotic measurement system for the accurate and automatic 3D measurement of large-scale components with complex curved surfaces. The system consists of the mobile optical scanning measurement device, visual tracking device, and software platform, which can realize comprehensive and accurate data acquisition and stitching of large-scale complex components. The combination of visual tracking and 3D measurement based on the coordinated motion of the dual robot achieved the automatic data acquisition of large-scale complex components without sticking coded targets. Additionally, this paper also introduces a DeepMerge algorithm that combines local and global features of the point cloud, which effectively corrects the initial stitching error of the visual tracking system. The validity of the measurement system and method was shown by the measurement and stitching experiments on the surface of the vehicle nose, ensuring the accurate measurement of the robot’s wide range of motion.

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A Mobile Robotic 3-D Measurement Method Based on Point Clouds Alignment for Large-Scale Complex Surfaces

Cited by 30 publications

References 29 publications

A Novel Generative Convolutional Neural Network for Robot Grasp Detection on Gaussian Guidance

A Novel Generative Convolutional Neural Network for Robot Grasp Detection on Gaussian Guidance

The Promotion and Optimization of Bank Financial Products Using Consumers’ Psychological Perception

Collaborative Measurement System of Dual Mobile Robots That Integrates Visual Tracking and 3D Measurement

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