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1 – 10 of 418Xiaohui Jia, Bin Zhao, Jinyue Liu and Shaolong Zhang
Traditional robot arm trajectory planning methods have problems such as insufficient generalization performance and low adaptability. This paper aims to propose a method to plan…
Abstract
Purpose
Traditional robot arm trajectory planning methods have problems such as insufficient generalization performance and low adaptability. This paper aims to propose a method to plan the robot arm’s trajectory using the trajectory learning and generalization characteristics of dynamic motion primitives (DMPs).
Design/methodology/approach
This study aligns multiple demonstration motion primitives using dynamic time warping; use the Gaussian mixture model and Gaussian mixture regression methods to obtain the ideal primitive trajectory actions. By establishing a system model that improves DMPs, the parameters of the nonlinear function are learned based on the ideal primitive trajectory actions of the robotic arm, and the robotic arm motion trajectory is reproduced and generalized.
Findings
Experiments have proven that the robot arm motion trajectory learned by the method proposed in this article can not only learn to generalize and demonstrate the movement trend of the primitive trajectory, but also can better generate ideal motion trajectories and avoid obstacles when there are obstacles. The maximum Euclidean distance between the generated trajectory and the demonstration primitive trajectory is reduced by 29.9%, and the average Euclidean distance is reduced by 54.2%. This illustrates the feasibility of this method for robot arm trajectory planning.
Originality/value
It provides a new method for the trajectory planning of robotic arms in unstructured environments while improving the adaptability and generalization performance of robotic arms in trajectory planning.
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Jun Zhao, Zhenguo Lu and Guang Wang
This study aims to address the challenge of the real-time state of charge (SOC) estimation for lithium-ion batteries in robotic systems, which is critical for monitoring remaining…
Abstract
Purpose
This study aims to address the challenge of the real-time state of charge (SOC) estimation for lithium-ion batteries in robotic systems, which is critical for monitoring remaining battery power, planning task execution, conserving energy and extending battery lifespan.
Design/methodology/approach
The authors introduced an optimal observer based on adaptive dynamic programming for online SOC estimation, leveraging a second-order resistor–capacitor model for the battery. The model parameters were determined by fitting an exponential function to the voltage response from pulse current discharges, and the observer's effectiveness was verified through extensive experimentation.
Findings
The proposed optimal observer demonstrated significant improvements in SOC estimation accuracy, robustness and real-time performance, outperforming traditional methods by minimizing estimation errors and eliminating the need for iterative steps in the adaptive critic and actor updates.
Originality/value
This study contributes a novel approach to SOC estimation using an optimal observer that optimizes the observer design by minimizing estimation errors. This method enhances the robustness of SOC estimation against observation errors and uncertainties in battery behavior, representing a significant advancement in battery management technology for robotic applications.
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Chia-Hua Lin, Dickson K.W. Chiu and Ki Tat Lam
This research investigates Hong Kong academic librarians' attitudes toward robotic process automation (RPA) and their willingness to learn this technology.
Abstract
Purpose
This research investigates Hong Kong academic librarians' attitudes toward robotic process automation (RPA) and their willingness to learn this technology.
Design/methodology/approach
This qualitative study collected data through one-on-one semi-structured interviews conducted with video conferencing software. After participants received basic RPA information and three existing library application cases, they answered questions based on the interview guide. This research used the inductive thematic analysis method to analyze the collected data.
Findings
Regarding Hong Kong academic librarians' attitudes towards RPA, 19 themes were identified. Although all participants did not have previous knowledge of RPA, most showed positive attitudes toward implementing RPA in their libraries and some willingness to learn it. Besides, among all identified themes, negative attitudes mainly comprised “Affect” and “Cognition” factors, hindering RPA deployment in academic libraries.
Originality/value
This research helps librarians and RPA vendors make better decisions or strategies for implementing RPA for libraries, which has not been explored, especially in East Asia.
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The aim of this paper is twofold: to explore the significance and implications of the rise of AI technology for the field of tertiary education in general and, in particular, to…
Abstract
Purpose
The aim of this paper is twofold: to explore the significance and implications of the rise of AI technology for the field of tertiary education in general and, in particular, to answer the question of whether teachers can be replaced by intelligent AI systems such as androids, what that requires in terms of human capabilities and what that might mean for teaching and learning in higher education.
Design/methodology/approach
Given the interdisciplinary nature of this conceptual paper, a literature review serves as a methodological tool to access data pertaining to the research question posed in the paper.
Findings
This exploratory paper gathers a range of evidence from the philosophy of mind (the mind-body problem), Kahneman’s (2011) System 1 and System 2 models of the mind, Gödel’s (1951) Two Incompleteness Theorems, Polanyi’s (1958, 1966) theory of tacit knowing and Searle’s (1980) Chinese Room thought experiment to the effect that no AI system can ever fully replace a human being because no machine can replicate the human mind and its capacity for intelligence, consciousness and highly developed social skills such as empathy and cooperation.
Practical implications
AI is rising, but there are inherent limits to what machines can achieve when compared to human capabilities. An android can at most attain “weak AI”, that is, it can be smart but lack awareness or empathy. Therefore, an analysis of good teaching at the tertiary level shows that learning, knowledge and understanding go far beyond any quantitative processing that an AI machine does so well, helping us to appreciate the qualitative dimension of education and knowledge acquisition. ChatGPT is robotic, being AI-generated, but human beings thrive on the human-to-human interface – that is, human relationships and meaningful connections – and that is where the true qualitative value of educational attainment will be gauged.
Social implications
This paper has provided evidence that human beings are irreplaceable due to our unique strengths as meaning-makers and relationship-builders, our capacity for morality and empathy, our creativity, our expertise and adaptability and our capacity to build unity and cooperate in building social structures and civilization for the benefit of all. Furthermore, as society is radically automated, the purpose of human life and its reevaluation will also come into question. For instance, as more and more occupations are replaced by ChatGPT services, more and more people will be freed up to do other things with their time, such as caring for relatives, undertaking creative projects, studying further and having children.
Originality/value
The investigation of the scope and limitations of AI is significant for two reasons. First, the question of the nature and functions of a mind becomes critical to the possibility of replication because if the human mind is like a super-sophisticated computer, then the relationship between a brain and mind is similar (if not identical) to the relationship between a computer as machine hardware and its programme or software (Dreyfus, 1979). [ ] If so, it should be theoretically possible to understand its mechanism and reproduce it, and then it is just a matter of time before AI research and development can replicate the human mind and eventually replace a human teacher, especially if an AI machine can teach just as intelligently yet more efficiently and economically. But if AI has inherent limitations that preclude the possibility of ever having a human-like mind and thought processes, then our investigation can at least clarify in what ways AI/AGI – such as ChatGPT – could support teaching and learning at universities.
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Bart Lameijer, Elizabeth S.L. de Vries, Jiju Antony, Jose Arturo Garza-Reyes and Michael Sony
Many organizations currently transition towards digitalized process design, execution, control, assurance and improvement, and the purpose of this research is to empirically…
Abstract
Purpose
Many organizations currently transition towards digitalized process design, execution, control, assurance and improvement, and the purpose of this research is to empirically demonstrate how data-based operational excellence techniques are useful in digitalized environments by means of the optimization of a robotic process automation deployment.
Design/methodology/approach
An interpretive mixed-method case study approach comprising both secondary Lean Six Sigma (LSS) project data together with participant-as-observer archival observations is applied. A case report, comprising per DMAIC phase (1) the objectives, (2) the main deliverables, (3) the results and (4) the key actions leading to achieving the presented results is presented.
Findings
Key findings comprise (1) the importance of understanding how to acquire and prepare large system generated data and (2) the need for better large system-generated database validation mechanisms. Finally (3) the importance of process contextual understanding of the LSS project lead is emphasized, together with (4) the need for LSS foundational curriculum developments in order to be effective in digitalized environments.
Originality/value
This study provides a rich prescriptive demonstration of LSS methodology implementation for RPA deployment improvement, and is one of the few empirical demonstrations of LSS based problem solving methodology in industry 4.0 contexts.
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Paloma Suárez-Brito, Patricia Esther Alonso-Galicia, Christian Fernando López-Orozco, José Carlos Vázquez-Parra and Edgar Omar López-Caudana
The objective of this proposal was to propose an educational innovation resource for the delivery of workshops with lesbian, gay, bisexual, transgender, queer, intersex and…
Abstract
Purpose
The objective of this proposal was to propose an educational innovation resource for the delivery of workshops with lesbian, gay, bisexual, transgender, queer, intersex and asexual (LGBTQIA) themes aimed at students in high school and middle school to promote complex thinking as a necessary competency for understanding their continuously changing environment.
Design/methodology/approach
Training for sexual and gender diversity challenges higher education institutions, some of which have bet on developing complex thinking to meet this need. Although not all universities have sufficient resources to create activities that foster relevant and diversity-sensitive competencies, some have implemented strategies ranging from modifying their curricula to designing specific classroom tasks that support student inclusion. In response to the challenges faced by higher education institutions (HEIs) to promote the acquisition of thinking skills for complexity, this paper proposes deploying a humanoid robot as an educational innovation tool in training initiatives that promote issues of sexual and gender diversity. The deployment model is described, considering design, delivery and evaluation. The value of this proposal lies in using humanoid robotics as a classroom resource within the framework of social robotics, considering its implications in the educational context to develop complex thinking competency and training for diversity in higher education students.
Findings
The data presented here highlight the importance of educational institutions integrating content into their plans, programs and activities (both curricular and extracurricular) that promote inclusion and sexual and gender diversity and attractive teaching strategies to reinforce this perspective. So, this proposal offers a support tool for implementing this content in everyday educational contexts where the objectives focus on triggering complex reasoning competencies.
Research limitations/implications
The varied responses and perceptions of students towards robotics and sexual diversity, as well as the lack of clear methods to assess educational outcomes, may compromise the effectiveness of the intervention.
Practical implications
The workshop proposed in this paper is configured as a series of iterations and repetitions in different educational fields, whether disciplinary (e.g. design or engineering) or transversal (e.g. entrepreneurship). The goal is to achieve educational strategies that generate a more significant impact at the institutional level. In this sense, the present proposal joins the actions implemented by other higher education institutions to make sexual and gender diversity visible to university students.
Social implications
The overall aim is to bring awareness, understanding and education to students with an inclusive, respectful and equitable perspective.
Originality/value
Social robotics is an innovative and attractive tool for young people at the higher education level. We consider our study a pioneer in the area.
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Hassan Younis, Omar M. Bwaliez, Mohammad Hamdan Garibeh and Balan Sundarakani
This study aims to investigate the impact of implementing various robotic systems in logistics and supply chain management on corporate performance in Jordanian manufacturing…
Abstract
Purpose
This study aims to investigate the impact of implementing various robotic systems in logistics and supply chain management on corporate performance in Jordanian manufacturing companies, focusing on environmental, operational, economic, and social dimensions.
Design/methodology/approach
Using a quantitative approach, data was collected through a survey questionnaire to measure the relationship between robotic systems and several performance dimensions. Various established constructs were employed, and the structural relationships were analyzed using partial least squares structural equation modeling (PLS-SEM) to assess the complex interdependencies within the model.
Findings
The results of this study indicate that the adoption of robotic systems has a positive influence on the environmental, operational, economic, and social performance of Jordanian manufacturing companies. In contrast to prior research that revealed inconsistencies in the social dimension, our findings align with previous studies highlighting the benefits of robotics in logistics and supply chain management. However, it’s worth noting that this study did not uncover similar inconsistencies, particularly in terms of the impact on social performance.
Practical implications
The study provides valuable insights for manufacturing companies considering the implementation of robotic systems, highlighting the need to evaluate the environmental, operational, social, and economic consequences. This understanding can help organizations make informed decisions to leverage the benefits of robotics for sustainable growth.
Originality/value
This study contributes to the growing literature on robotics in logistics and supply chain management, specifically focusing on the unique context of Jordanian manufacturing companies. By examining the multifaceted impact of robotic systems, this study extends the understanding of the role of technology in enhancing corporate performance.
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Pingyang Zheng, Shaohua Han, Dingqi Xue, Ling Fu and Bifeng Jiang
Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM…
Abstract
Purpose
Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.
Design/methodology/approach
Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.
Findings
The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.
Originality/value
The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.
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Baoxu Tu, Yuanfei Zhang, Wangyang Li, Fenglei Ni and Minghe Jin
The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment…
Abstract
Purpose
The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment requirements of deep learning methods on dexterous hands.
Design/methodology/approach
A distributed control architecture was designed, comprising embedded motion control subsystems and a host control subsystem built on ROS. The design of embedded controller state machines and clock synchronization algorithms ensured the stable operation of the entire distributed control system.
Findings
Experiments demonstrate that the entire system can operate stably at 1KHz. Additionally, the host can accomplish learning-based estimates of contact position and force.
Originality/value
This distributed architecture provides foundational support for the large-scale application of machine learning algorithms on dexterous hands. Dexterity hands utilizing this architecture can be easily integrated with robotic arms.
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Shan Shan Lu, Ruwen Tian and Dickson K.W. Chiu
The study aims to investigate the characteristics of the current situation of library programs and explore the possible reasons behind the low participation in Hong Kong. It…
Abstract
Purpose
The study aims to investigate the characteristics of the current situation of library programs and explore the possible reasons behind the low participation in Hong Kong. It focuses on the development of library programs in the era of digital technology, which can lead to discussion and reflections on the further development of library programs with innovative technology services.
Design/methodology/approach
This study applied a mixed-method research approach to investigate the current situation of library programming and the reasons for low participation in Hong Kong. The first part analyzes the characteristics of library programs offered by the Hong Kong Public Libraries (HKPL) through data collection from the HKPL website. The second part of this study investigated the reasons behind the low participation in library programs through quantitative research through an online survey.
Findings
The findings show that current library programs were dominated by reading activities and children's programs to a great extent, which both users and non-users are not very interested in. Further, most respondents expressed more interest in cultural and leisure events and hands-on activities (especially new technologies related) than traditional library programming. Many lapsed and non-users chose not to attend the library programs for boredom and uselessness. As a result, there is a need for HKPL to adjust its services to stay relevant to the needs and interests of local communities.
Originality/value
Scant studies explored the reasons behind non-users of public library programs, especially in Asia. This research contributes to the literature by analyzing and proposing the characteristics of the current situation of library programs and exploring the possible reasons behind the low participation in Hong Kong.
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