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Article
Publication date: 16 October 2017

Jiajun Li, Jianguo Tao, Liang Ding, Haibo Gao, Zongquan Deng, Yang Luo and Zhandong Li

The purpose of this paper is to extend the usage of stroke gestures in manipulation tasks to make the interaction between human and robot more efficient.

Abstract

Purpose

The purpose of this paper is to extend the usage of stroke gestures in manipulation tasks to make the interaction between human and robot more efficient.

Design/methodology/approach

In this paper, a set of stroke gestures is designed for typical manipulation tasks. A gesture recognition and parameter extraction system is proposed to exploit the information in stroke gestures drawn by the users.

Findings

The results show that the designed gesture recognition subsystem can reach a recognition accuracy of 99.00 per cent. The parameter extraction subsystem can successfully extract parameters needed for typical manipulation tasks with a success rate about 86.30 per cent. The system shows an acceptable performance in the experiments.

Practical implications

Using stroke gesture in manipulation tasks can make the transmission of human intentions to the robots more efficient. The proposed gesture recognition subsystem is based on convolutional neural network which is robust to different input. The parameter extraction subsystem can extract the spatial information encoded in stroke gestures.

Originality/value

The author designs stroke gestures for manipulation tasks which is an extension of the usage of stroke gestures. The proposed gesture recognition and parameter extraction system can make use of stroke gestures to get the type of the task and important parameters for the task simultaneously.

Details

Industrial Robot: An International Journal, vol. 44 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

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Article
Publication date: 5 June 2019

Hongjun Xing, Kerui Xia, Liang Ding, Haibo Gao, Guangjun Liu and Zongquan Deng

The purpose of this paper is to enable autonomous door-opening with unknown geometrical constraints. Door-opening is a common action needed for mobile manipulators to…

Abstract

Purpose

The purpose of this paper is to enable autonomous door-opening with unknown geometrical constraints. Door-opening is a common action needed for mobile manipulators to perform rescue operation. However, it remains difficult for them to handle it in real rescue environments. The major difficulties of rescue manipulation involve contradiction between unknown geometrical constraints and limited sensors because of extreme physical constraints.

Design/methodology/approach

A method for estimating the unknown door geometrical parameters using coordinate transformation of the end-effector with visual teleoperation assists is proposed. A trajectory planning algorithm is developed using geometrical parameters from the proposed method.

Findings

The relevant experiments are also conducted using a manipulator suited to extreme physical constraints to open a real door with a locked latch and unknown geometrical parameters, which demonstrates the validity and efficiency of the proposed approach.

Originality/value

This is a novel method for estimating the unknown door geometrical parameters with coordinate transformation of the end-effector through visual teleoperation assists.

Details

Assembly Automation, vol. 39 no. 3
Type: Research Article
ISSN: 0144-5154

Keywords

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Article
Publication date: 23 November 2020

Zhou Haitao, Haibo Feng, Li Xu, Songyuan Zhang and Yili Fu

The purpose of this paper is to improve control performance and safety of a real two-wheeled inverted pendulum (TWIP) robot by dealing with model uncertainty and motion…

Abstract

Purpose

The purpose of this paper is to improve control performance and safety of a real two-wheeled inverted pendulum (TWIP) robot by dealing with model uncertainty and motion restriction simultaneously, which can be extended to other TWIP robotic systems.

Design/methodology/approach

The inequality of lumped model uncertainty boundary is derived from original TWIP dynamics. Several motion restriction conditions are derived considering zero dynamics, centripedal force, ground friction condition, posture stability, control torque limitation and so on. Sliding-mode control (SMC) and model predictive control (MPC) are separately adopted to design controllers for longitudinal and rotational motion, while taking model uncertainty into account. The reference value of the moving velocity and acceleration, delivered to the designed controller, should be restricted in a specified range, limited by motion restrictions, to keep safe.

Findings

The cancelation of model uncertainty commonly existing in real system can improve control performance. The motion commands play an important role in maintaining safety and reliability of TWIP, which can be ensured by the proposed motion restriction to avoid potential movement failure, such as slipping, lateral tipping over because of turning and large fluctuation of body.

Originality/value

An inequation of lumped model uncertainty boundary incorporating comprehensive errors and uncertainties of system is derived and elaborately calculated to determine the switching coefficients of SMC. The motion restrictions for TWIP robot moving in 3D are derived and used to impose constraints on reference trajectory to avoid possible instability or failure of movement.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

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Article
Publication date: 14 August 2017

Xiaohui Wang and Haibo Wang

The purpose of the present research is to investigate the mechanisms by which conflict with customers (i.e. customer mistreatment) contributes to employees’ work withdrawal.

Abstract

Purpose

The purpose of the present research is to investigate the mechanisms by which conflict with customers (i.e. customer mistreatment) contributes to employees’ work withdrawal.

Design/methodology/approach

This paper tests its hypotheses by means of a field study of a sample of front-line health care workers in China. Data were collected in three waves over four months; a total of 398 health care workers completed the questionnaires and represented the final sample. A hierarchical multiple regression analysis was performed to test the proposed hypotheses.

Findings

The results indicate that mistreatment by customers contributes to employees’ work withdrawal, and emotional exhaustion serves as a mediator in this linkage. In addition, social support moderates the positive relation between customer mistreatment and employees’ emotional exhaustion, whereas conscientiousness moderates the positive relation between emotional exhaustion and withdrawal behavior.

Research limitations/implications

The sample used may not fully justify the generalizability of the research results. Without distinguishing different sources of social support may be another limitation. In addition, this study could be improved by using a multi-source survey design.

Practical implications

To help employees effectively cope with interpersonal conflict with customers, organizations should take action to promote communication between employees and their supervisors and coworkers. It is also advisable for organizations to adjust their selection strategies and hire front-line employees high in conscientiousness.

Originality/value

This research presents a resource-based framework to illuminate the detrimental effects of prolonged exposure to customer mistreatment on health care workers’ withdrawal behavior in Chinese context. Furthermore, this study examines factors that may serve to mitigate the harmful effects of customer mistreatment and regards workplace social support and conscientiousness as two different kinds of resources that can play dissimilar roles when employees are coping with customer mistreatment.

Details

International Journal of Conflict Management, vol. 28 no. 4
Type: Research Article
ISSN: 1044-4068

Keywords

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Article
Publication date: 7 August 2018

Haibo Huang, Jinpeng Liu, Binbin Fan, Xing Chen, Aibing Yu and Xuedao Shu

The purpose of this paper is to investigate the wear resistance behavior of the striated tool for cross wedge rolling (CWR).

Abstract

Purpose

The purpose of this paper is to investigate the wear resistance behavior of the striated tool for cross wedge rolling (CWR).

Design/methodology/approach

A mechanical-thermal coupled, temperature-dependent FE wear model was developed to explore the wear behaviors for striated CWR tools. To verify the proposed FE model, a newly developed measuring device was also developed to measure wear on the tool ridge. To find the impact order of the parameters of striate unit, orthogonal experiment was carried out.

Findings

The experimental and numerical results both indicate that the wear resistance of striated tool is better than that of smooth tool. Minimum tool ridge wear can be achieved by choosing proper tool contact temperature with striated units on crossed ridge. The order of the striation geometrical factors’ impact on ridge wear is striation width > striation interval > striation length.

Research limitations/implications

Because of the specified tool, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.

Originality/value

It is shown that the wear resistance of striated CWR tool is better than that of smooth tool. The information may help CWR manufactures to design and produce tools with less wear.

Details

Industrial Lubrication and Tribology, vol. 70 no. 6
Type: Research Article
ISSN: 0036-8792

Keywords

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Article
Publication date: 14 June 2019

Chao Liu, Mingyang Yang, Haoyu Han and Wenping Yue

To study fracture characteristics of jointed rock masses under blasting load, the RFPA2D analysis software for dynamic fracture of rocks based on the finite element method…

Abstract

Purpose

To study fracture characteristics of jointed rock masses under blasting load, the RFPA2D analysis software for dynamic fracture of rocks based on the finite element method and statistical damage theory was used.

Design/methodology/approach

On this basis, this research simulated the fracture process of rock masses in blasting with different joint geometrical characteristics and mainly analysed the influences of distance from joints to blasting holes, the length of joints, the number of joints and joint angle on fracture of rock masses.

Findings

The calculation results show that with the constant increase of the distance from joints to blasting holes, the influences of joints on blasting effects of rock masses gradually reduced. Rock masses with long joints experienced more serious damages than those with short joints. Damages obviously increased with the changing from rock masses without joints to rock masses with joints, and when there were three joints, the further increase of the number of joints had unobvious changes on blasting effects of rock masses. Joints showed significant guidance effect on the propagation of cracks in blasting: promoting propagation of main vertical cracks deflecting to the ends of joints.

Originality/value

The research results are expected to provide some theoretical bases in practical application of engineering blasting.

Details

Engineering Computations, vol. 36 no. 6
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 6 May 2021

Anbesh Jamwal, Rajeev Agrawal, Monica Sharma, Anil Kumar, Vikas Kumar and Jose Arturo Arturo Garza-Reyes

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of…

Abstract

Purpose

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of data generated from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM).

Design/methodology/approach

In the present study, the authors use a bibliometric review approach that is focused on the statistical analysis of published scientific documents with an unbiased objective of the current status and future research potential of ML applications in sustainable manufacturing.

Findings

The present study highlights how manufacturing industries can benefit from ML techniques when applied to address SM issues. Based on the findings, a ML-SM framework is proposed. The framework will be helpful to researchers, policymakers and practitioners to provide guidelines on the successful management of SM practices.

Originality/value

A comprehensive and bibliometric review of opportunities for ML techniques in SM with a framework is still limited in the available literature. This study addresses the bibliometric analysis of ML applications in SM, which further adds to the originality.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

Keywords

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Article
Publication date: 20 January 2021

Xueqing Zhao, Min Zhang and Junjun Zhang

Classifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human…

Abstract

Purpose

Classifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human eyes, which performs very low efficiency and high cost. Therefore, how to improve the classification accuracy of textile fabric defects by using current artificial intelligence and to better meet the needs in the textile industry, the purpose of this article is to develop a method to improve the accuracy of textile fabric defects classification.

Design/methodology/approach

To improve the accuracy of textile fabric defects classification, an ensemble learning-based convolutional neural network (CNN) method in terms of textile fabric defects classification (short for ECTFDC) on an enhanced TILDA database is used. ECTFDC first adopts ensemble learning-based model to classify five types of fabric defects from TILDA. Subsequently, ECTFDC extracts features of fabric defects via an ensemble multiple convolutional neural network model and obtains parameters by using transfer learning method.

Findings

The authors applied ECTFDC on an enhanced TILDA database to improve the robustness and generalization ability of the proposed networks. Experimental results show that ECTFDC outperforms the other networks, the precision and recall rates are 97.8%, 97.68%, respectively.

Originality/value

The ensemble convolutional neural network textile fabric defect classification method in this paper can quickly and effectively classify textile fabric defect categories; it can reduce the production cost of textiles and it can alleviate the visual fatigue of inspectors working for a long time.

Details

International Journal of Clothing Science and Technology, vol. 33 no. 4
Type: Research Article
ISSN: 0955-6222

Keywords

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