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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).

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.

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.

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.

This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations.

A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy.

The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems.

This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

The purpose of this study is to investigate the characteristic and function of oxide film formed on grinding wheel in electrolytic in-process dressing (ELID) precision grinding and improve the quality of ELID grinding.

Dynamic film forming experiments were carried out with a simulation device close to the actual processing conditions. Then, the ELID grinding experiments of bearing rings were performed using grinding wheels with good film forming effect. The experiment was designed by quadratic regression general rotation combination method. The influence of grinding depth, electrolytic voltage, duty cycle and grinding wheel linear speed on grinding effect is analyzed.

A mathematical model for the formation rate of oxide film was established. The experiments show that the composition of grinding wheel and grinding fluid, as well as the electrical parameters, influence the film forming effect. Thus, the oxide film plays an important role in ELID grinding.

This study provides a reference for the design and selection of grinding wheel and grinding fluid and the setting of process parameters in ELID grinding.

Urban spatial form influences the social, economic, and ecological development modes of the city. The spatial form during the urbanization of Hanjiang River Basin in Southern Shaanxi needs to be studied. In this study, research methodologies on urban spatial form in China and abroad were summarized. The concept of ecology background was applied, and the research framework for urban spatial form, which integrated the background, framework, core, axis, cluster, and skin, was established. Valley cities in the Hanjiang River Basin in Southern Shaanxi were classified into wide valley, narrow valley, and canyon cities. The spatial form characteristics of these three types of valley cities were discussed. A case study based on a typical city-Yang County-was conducted to discuss the characteristics of the aforementioned six elements of urban spatial form. Finally, spatial form characteristics were summarized. These characteristics provide a basis for the study of the small valley urban spatial form in the Hanjiang River Basin in Southern Shaanxi.

The purpose of this study is to provide insights into bootleg innovation by investigating whether perceived hindrance stressors play an important role in bootlegging and how different organizational ownership types (state-owned enterprises (SOEs) vs non-SOEs) affect this relationship.

The study samples comprised 3,967 employees from 674 knowledge-intensive companies in southern China. Multilevel structural equation modeling was used to test the hypotheses.

Drawing on the conservation of resources (COR) theory, the results show that hindrance stressors have a curvilinear (U-shaped) influence on bootleg innovation, and that the curve relationship between the hindrance stressors and bootlegging is more pronounced among employees in non-SOEs.

The findings indicate that either a low or high level of hindrance stressors can activate a high level of bootlegging activities among employees. These results suggest that managers need to be vigilant in detecting the level of hindrance because different motivations predominate at different stressor levels.

Based on the COR theory, the findings cast perceived hindrance stressors as an antecedent of bootlegging at the individual level. The inquiry into state ownership types further provides a comprehensive understanding of the non-linear relationship between hindrance stressors and bootlegging.

The purpose of this study is to investigate the heat resistance and heat-resistant oxygen aging of 4-nitrophthalonitrile-etherified cardanol-phenol-formaldehyde (PPCF) to further use and develop the resin as the matrix resin of high-temperature resistant adhesives and coatings.

PPCF resin was synthesized by 4-nitrophthalonitrile and cardanol-phenol-formaldehyde (PCF). The structures of PPCF and PCF were investigated by Fourier transform infrared, differential scanning calorimetry and proton nuclear magnetic resonance. In addition, the heat resistance and processability of PPCF and PCF resins were studied by dynamic mechanical analysis, thermogravimetric analysis, scanning electronic microscopy (SEM), X-ray diffraction (XRD) techniques and rheological studies.

The results reveal that PPCF forms a cross-linked network at a lower temperature. PPCF resin has excellent resistance under thermal aging in an air atmosphere and that it still had a certain residual weight after aging at 500°C for 2 h, whereas the PCF resin is completely decomposed.

4-Nitrophthalonitrile was introduced into PCF resin, and XRD and SEM were used to investigate the high temperature residual carbon rate and heat-resistant oxygen aging properties of PPCF and PCF resins.

The purpose of this paper is to demonstrate the theoretical relationship between the layout of four‐sensor dynamic acoustic array tracking system and systematic observation accuracy, and provide an algorithm to determine the optimal arrangement of four‐sensor acoustic array and an indicator to evaluate acoustic array system measurement accuracy.

In the present paper, the measurement principle of the four‐sensor dynamic acoustic array tracking system is analyzed, and the system observation model and the conversion relationship between models are established. Subsequently, the optimization algorithm for the four‐sensor dynamic acoustic array is deduced, the theoretical optimal arrangement of the four‐sensor dynamic acoustic array tracking measurement system is obtained based on the optimal position dilution of precision function (PDOPF) of 2D target, and the static experimental study on sound‐source bearing estimation is designed. The theoretical results are compared with the experimental results of the present study.

The measurement accuracy of the four‐sensor dynamic acoustic array tracking system is largely dependent on the layout of the acoustic sensor. Theoretical studies and experimental results demonstrated that an optimal PDPOF can be used to analyze the rationality of the layout. It can also serve as an indicator for the layout of the four‐sensor dynamic acoustic array tracking system.

The PDOPF value is presented as an indicator for the evaluation of the four‐sensor dynamic acoustic array systematic observation accuracy based on theoretical analysis. The feasibility of the indicator and the rationality of the sensor layout in practical engineering application are verified through experimental studies on sound‐source bearing estimation. The higher the PDOPF value is, the lower the accuracy of the system will be.

The purpose of this paper is to investigate the relationship between corporate governance mechanism and firm value of the listed companies in China. Does the better corporate governance lead to the higher firm value? Or does the higher firm value make it easy to choose a better governance mechanism? Or they affect each other? In other words, this paper tries to answer whether the corporate governance mechanism is only decided by institutional arrangement, or by market choice according to firm value or performance or by the interaction of institutional arrangement and market choice? It tries to answer whether institutional arrangement maximizes the firm value, or an invisible hand pushes them to arrive at its maximum.

This paper establishes an analytic framework of simultaneous equations based on causality, which includes five endogenous variables: ownership of larger shareholders, managerial ownership, director compensation, debt financing and firm value. It adopts 1,644 data samples from 274 Chinese listed companies in Shanghai and Shenzhen Stock Exchange during 2007- 2012 after the non-tradable shares reform. Ordinary least squares (OLS) estimation of single equation, 2SLS and 3SLS estimation of simultaneous equations are respectively done to show the differences of these three kinds of estimations.

The empirical results show that differences exist among OLS, 2SLS and 3SLS estimation. Finally, 3SLS estimation should be adopted because the OLS and 2SLS estimation are biased. There are endogenous relationships between corporate governance mechanism and firm value. Through the 3SLS estimation, it is found that first, ownership concentration and firm value affect each other positively. Second, managerial ownership and firm value affect each other positively; third, director compensation and firm value affect each other negatively, while director compensation and firm performance affect each other positively. Finally, debt financing level and firm value are negatively related to each other.

It means that ownership of large shareholders, managerial ownership, director compensation and debt financing in the Chinese listed companies are found to have a root in the interaction between institutional arrangement and market choice. It is also found that adverse selection occurs when creditors loan to the listed companies. Managerial compensation is positively related to accounting profit, but it is negatively related to firm value because managers increase profit due by earning management. This could only increase the accounting profits and obtain huge cash compensation, but not increase firm value and even harm the interests of shareholders.

This paper not only shows the difference between OLS and 2SLS estimation but also compares the estimation of 2SLS and 3SLS in terms of empirical methods. It gives answers to the following questions: whether the relationship is one-way causality or bilateral causality between ownership concentration, managerial ownership, director compensation and firm value; whether governance mechanism affects firm value by institutional arrangement, or market drives both of them to strike a balance by an invisible hand. In other words, does it make them arrive at equilibrium through the competitive selection process when shareholders, directors, managers and creditors attempt to maximize themselves of their interests?

Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services.

Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage.

The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration.

This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.