Search results

1 – 10 of over 1000
Article
Publication date: 21 August 2023

Minghao Wang, Ming Cong, Yu Du, Dong Liu and Xiaojing Tian

The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and…

Abstract

Purpose

The purpose of this study is to solve the problem of an unknown initial position in a multi-robot raster map fusion. The method includes two-dimensional (2D) raster maps and three-dimensional (3D) point cloud maps.

Design/methodology/approach

A fusion method using multiple algorithms was proposed. For 2D raster maps, this method uses accelerated robust feature detection to extract feature points of multi-raster maps, and then feature points are matched using a two-step algorithm of minimum Euclidean distance and adjacent feature relation. Finally, the random sample consensus algorithm was used for redundant feature fusion. On the basis of 2D raster map fusion, the method of coordinate alignment is used for 3D point cloud map fusion.

Findings

To verify the effectiveness of the algorithm, the segmentation mapping method (2D raster map) and the actual robot mapping method (2D raster map and 3D point cloud map) were used for experimental verification. The experiments demonstrated the stability and reliability of the proposed algorithm.

Originality/value

This algorithm uses a new visual method with coordinate alignment to process the raster map, which can effectively solve the problem of the demand for the initial relative position of robots in traditional methods and be more adaptable to the fusion of 3D maps. In addition, the original data of the map can come from different types of robots, which greatly improves the universality of the algorithm.

Details

Robotic Intelligence and Automation, vol. 43 no. 5
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 7 September 2023

Minghao Wang, Ming Cong, Dong Liu, Yu Du, Xiaojing Tian and Bing Li

The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic…

Abstract

Purpose

The purpose of this study is to designed a robot odometry based on three dimensional (3D) laser point cloud data, inertial measurement unit (IMU) data and real-time kinematic (RTK) data in underground spatial features and gravity fluctuations environment. This method improves the mapping accuracy in two types of underground space: multi-layer space and large-scale scenarios.

Design/methodology/approach

An IMU–Laser–RTK fusion mapping algorithm based on Iterative Kalman Filter was proposed, and the observation equation and Jacobian matrix were derived. Aiming at the problem of inaccurate gravity estimation, the optimization of gravity is transformed into the optimization of SO(3), which avoids the problem of gravity over-parameterization.

Findings

Compared with the optimization method, the computational cost is reduced. Without relying on the wheel speed odometer, the robot synchronization localization and 3D environment modeling for multi-layer space are realized. The performance of the proposed algorithm is tested and compared in two types of underground space, and the robustness and accuracy in multi-layer space and large-scale scenarios are verified. The results show that the root mean square error of the proposed algorithm is 0.061 m, which achieves higher accuracy than other algorithms.

Originality/value

Based on the problem of large loop and low feature scale, this algorithm can better complete the map loop and self-positioning, and its root mean square error is more than double compared with other methods. The method proposed in this paper can better complete the autonomous positioning of the robot in the underground space with hierarchical feature degradation, and at the same time, an accurate 3D map can be constructed for subsequent research.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Book part
Publication date: 14 December 2023

Mcxin Tee, Lee-Yen Chaw and Sadia Mehfooz Khan

Sustainable tourism will be an appropriate strategy to be promoted during the post COVID-19 pandemic, as this is a turning point for the tourism industry to grab the unique chance…

Abstract

Sustainable tourism will be an appropriate strategy to be promoted during the post COVID-19 pandemic, as this is a turning point for the tourism industry to grab the unique chance to have a true reset by focussing on achieving long-term sustainability and a shift from a ‘me to we’ economy. To support sustainable tourism and foster future success in the tourism industry, the process of integrating green knowledge and knowledge management can begin with entrepreneurial education in higher education institutions (HEIs). However, empirical research on university students' green entrepreneurial intention in sustainable tourism has not been exhaustively studied. Additionally, there is a need to further explore knowledge management process and entrepreneurial learning in HEIs. Hence, the aim of this study is to analyze knowledge management as a technique to explore the green entrepreneurial intention of students in HEIs in sustaining Malaysia's tourism post COVID-19 pandemic. Exploratory research with quantitative analysis was conducted through partial least squares structural equation modelling (PLS-SEM). The findings reveal that there is a positive and significant relationship between green entrepreneurial knowledge and green entrepreneurial intention in sustainable tourism among university business students. Additionally, knowledge revision and conceptual change positively and significantly influence green entrepreneurial knowledge and green entrepreneurial intention in sustainable tourism. However, knowledge application has no impact on green entrepreneurial knowledge and green entrepreneurial intention. The results of this study also reveal that green entrepreneurial knowledge does not have a mediation effect on green entrepreneurial intention. The present work contributes by going beyond the study of entrepreneurial intention, as the research focusses on interconnection among these three major areas: knowledge management, sustainable tourism, and entrepreneurship education post COVID-19 pandemic. Hence, the combination of these diverse aspects in this study provides insights to educators and policy makers to investigate the importance of green entrepreneurial knowledge and benefits of knowledge management that can be integrated into entrepreneurship education for current and future sustainable tourism development.

Article
Publication date: 4 August 2023

Zhiqi Liu, Tanghong Liu, Hongrui Gao, Houyu Gu, Yutao Xia and Bin Xu

Constructing porous wind barriers is one of the most effective approaches to increase the running safety of trains on viaducts in crosswinds. This paper aims to further improve…

Abstract

Purpose

Constructing porous wind barriers is one of the most effective approaches to increase the running safety of trains on viaducts in crosswinds. This paper aims to further improve the wind-sheltering performance of the porous wind barriers.

Design/methodology/approach

Improved delayed detached eddy simulations based on the k-ω turbulence model were carried out, and the results were validated with wind tunnel tests. The effects of the hole diameter on the flow characteristics and wind-sheltering performance were studied by comparing the wind barriers with the porosity of 21.6% and the hole diameters of 60 mm–360 mm. The flow characteristics above the windward and leeward tracks were analyzed, and the wind-sheltering performance of the wind barriers was assessed using the wind speed reduction coefficients.

Findings

The hole diameters affected the jet behind the wind barriers and the recirculation region above the tracks. Below the top of the wind barriers, the time-averaged velocity first decreased and then increased with the increase in the hole diameter. The wind barrier with the hole diameter of 120 mm had the best wind-sheltering performance for the windward track, but such barrier might lead to overprotection on the leeward track. The wind-sheltering performance of the wind barriers with the hole diameters of 240 mm and 360 mm was significantly degraded, especially above the windward track.

Originality/value

The effects of the hole diameters on the wake and wind-sheltering performance of the wind barriers were studied, by which the theoretical basis is provided for a better design of the porous wind barrier.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 33 no. 11
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 28 November 2022

Cuijuan Liu, Zhenxin Xiao, Yu Gao, Maggie Chuoyan Dong and Shanxing Gao

Although manufacturer-initiated rewards are widely used to secure distributors’ compliance, the spillover effect on unrewarded distributors (i.e. observers) in the same…

Abstract

Purpose

Although manufacturer-initiated rewards are widely used to secure distributors’ compliance, the spillover effect on unrewarded distributors (i.e. observers) in the same distribution channel is under-researched. Using insights from social learning theory, this paper aims to investigate how manufacturer-initiated rewards affect observers’ expectation of reward and shape observers’ compliance toward the manufacturer. Furthermore, this paper explores how such effects are contingent upon distributor relationship features.

Design/methodology/approach

To test the hypotheses, hierarchical multiple regression and bootstrapping analyses were performed using survey data from 280 Chinese distributors.

Findings

The magnitude of a manufacturer-initiated reward to a distributor stimulates expectation of reward among observers, which enhances compliance; observers’ expectation of reward mediates the impact of reward magnitude on compliance. Moreover, network centrality (of the rewarded peer) negatively moderates the positive impact of reward magnitude on observers’ expectation of reward, whereas observers’ dependence (on the manufacturer) positively moderates this dynamic.

Practical implications

Manufacturers should pay attention to the spillover effects of rewards. Overall, they should use rewards of appropriate magnitude to show willingness to recognize outstanding distributors. This will inspire unrewarded distributors, which will then be more compliant. Furthermore, manufacturers should know that specific types of distributor relationship features may significantly vary the spillover effects.

Originality/value

This study illuminates the spillover effects of manufacturer-initiated reward by opening the “black box” of the link between reward magnitude and observers’ compliance and by specifying the effects’ boundary conditions.

Details

Journal of Business & Industrial Marketing, vol. 38 no. 10
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 5 September 2023

Weihua Liu, Zhixuan Chen, Tsan-Ming Choi, Paul Tae-Woo Lee, Hing Kai Chan and Yongzheng Gao

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

448

Abstract

Purpose

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

Design/methodology/approach

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Findings

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

Practical implications

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

Originality/value

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

Details

International Journal of Operations & Production Management, vol. 44 no. 4
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 30 January 2024

Shaonan Shi, Feixiang Tang, Yongqiang Yu, Yuzheng Guo, Fang Dong and Sheng Liu

Hoping to uncover the physical principles of the vibration of the functionally graded material (FGM) microplate, by which the authors can make contributions to the design and…

Abstract

Purpose

Hoping to uncover the physical principles of the vibration of the functionally graded material (FGM) microplate, by which the authors can make contributions to the design and manufacturing process in factories like micro-electro-mechanical system (MEMS) and other industries.

Design/methodology/approach

The authors design a method by establishing a reasonable mathematical model of the physical microplate composed of a porous FGM.

Findings

The authors discover that the porosity, the distributions of porosity, the power law of the FGM and the length-to-thickness ratio all affect the natural frequency of the vibration of the microplate, but in different ways.

Originality/value

Originally proposed a model of the micro FGM plate considering the different distributions of the porosity and scale effect and analyzed the vibration frequency of it.

Details

Multidiscipline Modeling in Materials and Structures, vol. 20 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 20 October 2023

Mohamed M. Elsotouhy, Mohamed A. Ghonim, Nada Khalifa and Mohamed A. Khashan

Despite the importance of emotional variables in shaping individuals' consumption behavior, nature-love still needs to be addressed concerning various aspects of sustainable…

Abstract

Purpose

Despite the importance of emotional variables in shaping individuals' consumption behavior, nature-love still needs to be addressed concerning various aspects of sustainable consumption behavior (SCB). Considering the dimensions of nature-love, this study aims to investigate the effect of passion-for-nature, intimacy-with-nature and commitment-to-nature on SCB. Furthermore, this study aims to incorporate the construal levels of psychological distance (PD) as a moderating variable between the tested variables to add a more in-depth understanding.

Design/methodology/approach

Data was collected from a sample of 311 individuals from Egypt using the snowball sampling method and the ten-time rule technique. The data was analyzed using partial least squares-structural equation modeling (PLS-SEM).

Findings

The findings indicate that passion-for-nature and intimacy-with-nature have a significant positive effect on green purchasing, reusability and recycling. On the other hand, commitment-to-nature has a significant positive effect on both green purchasing and reusability. Additionally, a high PD acts as a moderator between the relationships tested. The findings have been discussed in terms of their theoretical and practical implications.

Originality/value

To the best of the authors’ knowledge, this is the first study to integrate PD as a moderator between the relationships tested. Additionally, this paper is the first empirical research investigating these relationships in developing economies.

Details

EuroMed Journal of Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1450-2194

Keywords

Article
Publication date: 25 March 2024

Boyang Hu, Ling Weng, Kaile Liu, Yang Liu, Zhuolin Li and Yuxin Chen

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using…

Abstract

Purpose

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

Design/methodology/approach

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

Findings

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

Research limitations/implications

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

Practical implications

A new approach to gesture recognition using wearable devices.

Social implications

This study has a broad application prospect in the field of human–computer interaction.

Originality/value

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

Details

Sensor Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0260-2288

Keywords

Article
Publication date: 18 January 2024

Zaihua Luo, Juliang Xiao, Sijiang Liu, Mingli Wang, Wei Zhao and Haitao Liu

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too…

Abstract

Purpose

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too many identification parameters, complex model, difficult convergence of optimization algorithms and easy-to-fall into a locally optimal solution, and improve the efficiency and accuracy of dynamic parameter identification.

Design/methodology/approach

First, the dynamic parameter identification model of the 5-DOF hybrid robot was established based on the principle of virtual work. Then, the sensitivity of the parameters to be identified is analyzed by Sobol’s sensitivity method and verified by simulation. Finally, an identification strategy based on sensitivity analysis was designed, experiments were carried out on the real robot and the results were verified.

Findings

Compared with the traditional full-parameter identification method, the dynamic parameter identification method based on sensitivity analysis proposed in this paper converges faster when optimized using the genetic algorithm, and the identified dynamic model has higher prediction accuracy for joint drive forces and torques than the full-parameter identification models.

Originality/value

This work analyzes the sensitivity of the parameters to be identified in the dynamic parameter identification model for the first time. Then a parameter identification method is proposed based on the results of the sensitivity analysis, which can effectively reduce the parameters to be identified, simplify the identification model, accelerate the convergence of the optimization algorithm and improve the prediction accuracy of the identified model for the joint driving forces and torques.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

1 – 10 of over 1000