Search results

This paper aims to deal with the force and position tracking problem when a robot performs a task in interaction with an unknown environment and presents a hybrid control strategy based on variable admittance control and fixed-time control.

A hybrid control strategy based on variable admittance control and fixed-time control is presented. Firstly, a variable stiffness admittance model control based on proportional integral and differential (PID) is adopted to maintain the expected force value during the task execution. Secondly, a fixed-time controller based on radial basis function neural network (RBFNN) is introduced to handle the model uncertainties and ensure the fast position tracking convergence of the robot system, while the singularity problem is also avoided by designing the virtual control variable with piecewise function.

Simulation studies conducted on the robot manipulator with two degrees of freedom have verified the superior performance of the proposed control strategy comparing with other methods.

A hybrid control scheme for robot–environment interaction is presented, in which the variable stiffness admittance method is adopted to adjust the interaction force to the desired value, and the RBFNN-based fixed-time position controller without singularity problem is designed to ensure the fast convergence of the robot system with model uncertainty.

Teaching by demonstration (TbD) is a promising way for robot learning skills in human and robot collaborative hybrid manufacturing lines. Traditionally, TbD systems have only concentrated on how to enable robots to learn movement skills from humans. This paper aims to develop an extended TbD system which can also enable learning stiffness regulation strategies from humans.

Here, the authors propose an extended dynamical motor primitives (DMP) framework to achieve this goal. In addition to the advantages of the traditional ones, the authors’ framework can enable robots to simultaneously learn stiffness and the movement from human demonstrations. Additionally, Gaussian mixture model (GMM) is used to capture the features of movement and of stiffness from multiple demonstrations of the same skill. Human limb surface electromyography (sEMG) signals are estimated to obtain the reference stiffness profiles.

The authors have experimentally demonstrated the effectiveness of the proposed framework. It shows that the authors approach could allow the robot to execute tasks in a variable impedance control mode with the learned movement trajectories and stiffness profiles.

In robot skill acquisition, DMP is widely used to encode robotic behaviors. So far, however, these DMP modes do not provide the ability to properly represent and generalize stiffness profiles. The authors argue that both movement trajectories and stiffness profiles should be considered equally in robot skill learning. The authors’ approach has great potential of applications in the future hybrid manufacturing lines.

The purpose of this paper is to present a method which enables a robot to learn both motion skills and stiffness profiles from humans through kinesthetic human-robot cooperation.

Admittance control is applied to allow robot-compliant behaviors when following the reference trajectories. By extending the dynamical movement primitives (DMP) model, a new concept of DMP and stiffness primitives is introduced to encode a kinesthetic demonstration as a combination of trajectories and stiffness profiles, which are subsequently transferred to the robot. Electromyographic signals are extracted from a human’s upper limbs to obtain target stiffness profiles. By monitoring vibrations of the end-effector velocities, a stability observer is developed. The virtual damping coefficient of admittance controller is adjusted accordingly to eliminate the vibrations.

The performance of the proposed methods is evaluated experimentally. The result shows that the robot can perform tasks in a variable stiffness mode as like the human dose in the teaching phase.

DMP has been widely used as a teaching by demonstration method to represent movements of humans and robots. The proposed method extends the DMP framework to allow a robot to learn not only motion skills but also stiffness profiles. Additionally, the authors proposed a stability observer to eliminate vibrations when the robot is disturbed by environment.

This study aims to focus on the authority formation process of Chinese enterprise leaders, with the purpose of finding out how an ordinary newly established firm leader develops into a real top leader and achieves the status of legitimacy in a well-known enterprise.

Based on constructivist grounded theory, this paper investigates the formation mechanism of entrepreneurial authority in China by using the rich data of Liu Chuan-zhi’s leader activities.

In the “evolution” path of authority formation, leaders continually consolidate and improve their authority through two classes of exceptional management activities: “emergency rescue” and “promotion activities”. The successful realization of exceptional management activities benefits from a leader’s management experience accumulation and relationship maintenance with the government. In the “design” path of authority formation, leaders consolidate and improve their authority by exercising their position of power. Leaders’ legitimacy is reflected by making strategic decision and demonstrating discretion of position power. Additionally, passing on an inspiring leader’s thoughts and ideas to an organization’s members is accomplished through the construction of organization culture, institutionalization and convention.

First, the findings are based on only Liu Chuan-zhi’s case. The authors still need more cases to compare and develop the findings and seek theoretical saturation in a broader sense. Second, the qualitative analysis is based on secondary data and future research could consider the introduction of interviews, video and other types of research data.

Under the parallel paths which are “evolution” and “design”, the dynamic leader authority formation model in China is founded.

Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.

A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.

The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.

This study has positive implications for enriching the method system of multivariable grey prediction model.

Marketing, entrepreneurship, operations management, and transportation/logistics.

The case is suitable for junior, senior undergraduate and first-year graduate business classes. It can be used entirely in business classes in marketing, entrepreneurship, operations management, and transportation/logistics, and parts of it can be used for discussions in classes related to emerging economies/markets, environmental management, sustainability, and technology management.

The case builds on the expansion plan considered by a young software company, called Hangzhou Omnipay located in the city of Hangzhou, China. Mr Chao, Vice President (VP) of Omnipay, is the main character of the case. He was aware of the current car-sharing industry leader – Zipcar headquartered in Boston and also identified multiple stakeholders in the city for decision making. By collaborating with a global student project team, Mr Chao collected a great deal of information and data. This teaching case provides students and educators ample opportunities to examine, from a multitude of aspects, the viability of a car-sharing service in Hangzhou.

The central goal is to help students gain a comprehensive understanding of the role of car-sharing service in a country's development in sustainability, socio-economy, environmental commitment, and new urban life style, as well as in a technological company's active pursuit of business expansion opportunity. In addition, students will not only understand the social, cultural, technological and strategic perspectives of car-sharing service implementation, but also develop and enhance analytic skills needed to conduct fundamental cost analysis, determine a base-line pricing scheme, and service location network design.

Teaching notes are available, please contact your librarian for access.

As laser scanning technology becomes readily available and affordable, there is an increasing demand of using point cloud data collected from a laser scanner to create as-built building information modeling (BIM) models for quality assessment, schedule control and energy performance within construction projects. To enhance the as-built modeling efficiency, this study explores an integrated system, called Auto-Scan-To-BIM (ASTB), with an aim to automatically generate a complete Industry Foundation Classes (IFC) model consisted of the 3D building elements for the given building based on its point cloud without requiring additional modeling tools.

ASTB has been developed with three function modules. Taking the scanned point data as input, Module 1 is built on the basis of the widely used region segmentation methodology and expanded with enhanced plane boundary line detection methods and corner recalibration algorithms. Then, Module 2 is developed with a domain knowledge-based heuristic method to analyze the features of the recognized planes, to associate them with corresponding building elements and to create BIM models. Based on the spatial relationships between these building elements, Module 3 generates a complete IFC model for the entire project compatible with any BIM software.

A case study validated the ASTB with an application with five common types of building elements (e.g. wall, floor, ceiling, window and door).

First, an integrated system, ASTB, is developed to generate a BIM model from scanned point cloud data without using additional modeling tools. Second, an enhanced plane boundary line detection method and a corner recalibration algorithm are developed in ASTB with high accuracy in obtaining the true surface planes. At last, the research contributes to develop a module, which can automatically convert the identified building elements into an IFC format based on the geometry and spatial relationships of each plan.

The purpose of this study is to provide an alternative approach to teacher learning on top of the usual practices of listening to experts' lectures and conducting school-based activities among peers in China. A boundary-crossing lesson study (BCLS) through school-university partnership served as an example to illustrate how a class teacher's mindset changed towards her students in equal interactions with university scholars.

With the lenses of action science theory and boundary-crossing learning theory, the study used qualitative research approach to collect and analyze data. One Chinese primary school class teacher from a workshop on narrative action research was selected as the case for this study. Interviewing, observation and document analysis were used to collect data. Data analysis methods included categorization and contextualization of the teacher's mindset change towards her student.

The case teacher, Mrs. Li, collaborated closely in paired teaching with her university partner AP Yu in all the four phases of their BCLS. Each phase was marked with an interactive event such as dialogic illumination, reflexive theorization, embodied conversation, and fusion of teacher and trainer roles. With inspirational trust as a major interactive mechanism, Mrs. Li jumped out of her single-loop learning (changing strategies according to results) to double-loop learning (changing both strategies and values/values). As a result, her mindset changed from attribution to appreciation towards her low-achieving student.

This study made contributions in two ways. First, it examined a class teacher's mindset change towards her student, rather than that of subject matter teachers towards their teaching materials and methods. Second, it revealed how reflective interactions in a special kind of BCLS by school teachers and university scholars may promote the teacher's mindset change. The findings further confirm that having differences as boundaries is not enough for teacher learning. For deep learning like Mrs. Li's mindset change, it requires a respectful and inspirational relationship between school teachers and university scholars in the BCLS.

The Chinese government launched the “going abroad” policy in 2001 to encourage Chinese companies to invest and create Chinese brands in international markets. However, the perceptions of Chinese brands among Western consumers have been shown to be consistently low, especially among European consumers. This research aims to investigate the Irish consumers' perception of Chinese brands and how to improve the “Made in China” image. This paper also investigates consumers' perceptions and attitudes when making purchase decisions for Chinese brands based on gender, age, and nationality. The paper provides important recommendations for Chinese companies who plan to enter the European, and more particularly, the Irish market.