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The results of obstacle avoidance path planning for the manipulator using artificial potential field (APF) method contain a large number of path nodes, which reduce the efficiency of manipulators. This paper aims to propose a new intelligent obstacle avoidance path planning method for picking robot to improve the efficiency of manipulators.

To improve the efficiency of the robot, this paper proposes a new intelligent obstacle avoidance path planning method for picking robot. In this method, we present a snake-tongue algorithm based on slope-type potential field and combine the snake-tongue algorithm with genetic algorithm (GA) and reinforcement learning (RL) to reduce the path length and the number of path nodes in the path planning results.

Simulation experiments were conducted with tomato string picking manipulator. The results showed that the path length is reduced from 4.1 to 2.979 m, the number of nodes is reduced from 31 to 3 and the working time of the robot is reduced from 87.35 to 37.12 s, after APF method combined with GA and RL.

This paper proposes a new improved method of APF, and combines it with GA and RL. The experimental results show that the new intelligent obstacle avoidance path planning method proposed in this paper is beneficial to improve the efficiency of the robotic arm.

Figure 1 According to principles of bionics, we propose a new path search method, snake-tongue algorithm, based on a slope-type potential field. At the same time, we use genetic algorithm to strengthen the ability of the artificial potential field method for path searching, so that it can complete the path searching in a variety of complex obstacle distribution situations with shorter path searching results. Reinforcement learning is used to reduce the number of path nodes, which is good for improving the efficiency of robot work. The use of genetic algorithm and reinforcement learning lays the foundation for intelligent control.

For robots to more actively interact with the surrounding environment in object manipulation tasks or walking, they must understand the physical attributes of objects and surface materials they encounter. Dynamic tactile sensing can effectively capture rich information about material properties. Hence, methods that convey and interpret this tactile information to the user can improve the quality of human–machine interaction. This paper aims to propose a visual-tactile cross-modal retrieval framework to convey tactile information of surface material for perceptual estimation.

The tactile information of a new unknown surface material can be used to retrieve perceptually similar surface from an available surface visual sample set by associating tactile information to visual information of material surfaces. For the proposed framework, the authors propose an online low-rank similarity learning method, which can effectively and efficiently capture the cross-modal relative similarity between visual and tactile modalities.

Experimental results conducted on the Technischen Universität München Haptic Texture Database demonstrate the effectiveness of the proposed framework and the method.

This paper provides a visual-tactile cross-modal perception method for recognizing material surface. By the method, a robot can communicate and interpret the conveyed information about the surface material properties to the user; it will further improve the quality of robot interaction.

This paper aims to perform the real-time and accurate ergonomics analysis for the operator in the manual assembly, with the purpose of identifying potential ergonomic injuries when encountering labor-excessive and unreasonable assembly operations.

Instead of acquiring body data for ergonomic evaluation by arranging many observers around, this paper proposes a multi-sensor based wearable system to track worker’s posture for a continuous ergonomic assessment. Moreover, given the accurate neck postural data from the shop floor by the proposed wearable system, a continuous rapid upper limb assessment method with robustness to occasional posture changes, is proposed to evaluate the neck and upper back risk during the manual assembly operations.

The proposed method can retrieve human activity data during manual assembly operations, and experimental results illustrate that the proposed work is flexible and accurate for continuous ergonomic assessments in manual assembly operations.

Based on the proposed multi-sensor based wearable system for posture acquisition, a real-time and high-precision ergonomics analysis is achieved with the postural data arrived continuously, it can provide a more objective indicator to assess the ergonomics during manual assembly.

The purpose of this paper is to present a family of robust metasurface-oriented wireless power transfer systems with improved efficiency and size compactness. The effect of geometric and structural features on the overall efficiency and miniaturisation is elaborately studied, while the presence of substrate losses is, also, considered. Moreover, to further enhance the performance, possible means for reducing the operating frequency, without comprising the unit-cell size, are proposed.

The key element of the design technique is the edge-coupled split-ring resonators patterned in various metasurface configurations and optimally placed to increase the total efficiency. To this goal, a rigorous three-dimensional algorithm, launching a new high-order prism macroelement, is developed in this paper for the fast evaluation of the required quantities. The featured scheme can host diverse approximation orders, while it is drastically more economical than existing methods. Hence, the demanding wireless power transfer systems are precisely modelled via reduced degrees of freedom, without the need to conduct large-scale simulations.

Numerical results, compared with measured data from fabricated prototypes, validate the design methodology and prove its competence to provide enhanced metasurface wireless power transfer systems. An assortment of optimized 3 x 3 and 5 x 5 metamaterial setups is investigated, and interesting deductions, regarding the impact of the inter-element gaps, the distance between the transmitting and receiving components and the substrate losses, are derived. Also, the proposed vector macroelement technique overwhelms typical implementations in terms of computational burden, particularly when combined with the relevant commercial software packages.

Systematic design of advanced real-world wireless power transfer structures through optimally selected metasurfaces with fully controllable electromagnetic properties is presented. The analysis is performed by means of a rapid prism macroelement methodology, which leads to very confined meshes, accurate results and significantly reduced overhead. The selected metamaterial resonators are found to be very flexible and reconfigurable, even in the case of large substrate conductivity losses, whereas their contribution to the system’s total efficiency is decisive.

For large projects, project segmentation and planning the size of contract packages in construction bids is a complex and critical issue. Due to the nature of construction projects, which frequently have large budgets, long durations and many activities with complex procedures, project segmentation involves complicated decision-making. To fill this gap, this study aims to develop an integrated model for planning project segmentation.

The proposed model integrates a simulation and multiple attribute decision-making method. The simulation is used to evaluate the bidding outcome of various project segmentations. The owner can then determine the bid-price behavior of contractors in response to varying work package sizes. The multiple attribute decision-making method is used to select the optimal segmentation solution from the simulated scenarios.

The proposed model is applied to a large road preservation project in Indonesia and incorporates bid participants and market conditions. The model provides seven scenarios for segmentation. The range of scenarios captures increasing competitiveness in the construction with the average bid price becoming gradually more beneficial for the owner. The model also utilizes a multiple attribute decision-making method to select the optimum scenario for the owner.

This study presents an applicable model for project segmentation that is useful for both project owners and contractors. By utilizing the proposed model, a project owner can segment a large project into smaller contract packages to create improved project pricing.

The purpose of this paper is to present a conceptual model of guanxi‐oriented human resource management (HRM) appropriate for organisations located in China that wish to maximise knowledge sharing and exchange. The recognised need by Western‐based organisations to develop trusting relationships through appropriate HRM approaches presents the setting to introduce the importance of guanxi in Chinese culture. The added complexity for Chinese organisations that employ a diversity of what are termed, in this paper, Conventional and Foreign Educated Chinese and Acculturated and Newly Arrived Expatriates is also presented.

Building on a review of literature about what challenges the knowledge revolution is having on the way that Western organisations manage their human resources, the paper presents an overview of the notion and function of guanxi in the Chinese context. The paradoxical and ambiguous nature of guanxi and its implications for interpersonal interactions are explained as being important for HR practitioners to understand.

The paper presents a conceptual guanxi‐oriented HRM model that incorporates the Chinese mindset that is, at one and the same time, paradoxical, holistic, dynamic, interdependent, flexible and reciprocal in nature.

While conceptual, the paper is based on a model developed from research by one of the authors that identified a guanxi‐oriented model of conflict resolution. The paper acknowledges that this model requires further research to test its applicability.

The paper is original in its attempt to link guanxi to HRM practices on Western concepts of human resources.

This paper aims to make a call for the establishment of a new research journal: a likely title for which would be Chinese Public Management. The background to this is clearly set out here for posterity’s sake. The review of selected papers unveils an emerging trend amongst Chinese researchers for undertaking deeper, cluster-based analyses. See, for example, the insights presented in this issue concerning competitiveness in China’s automobile industry.

A diary-like account has been made of the series of recent events that sparked the author’s interest in creating a journal to be known as Chinese Public Management. Why is there currently this focus on empirical research for public policy? From the author’s five years’ work for a serial visiting professorship across China, he has found that there are now well-established, substantial databases dedicated to the subject. Even more importantly – as this paper illustrates – a growing community of scholars has become keen to embark upon an in-depth, quantitative research. Perhaps, for the new journal, we would need an editor concentrating specifically on databases. Furthermore, undertaking scholarly work that is still of practical relevance for guiding authorities in their formulations of public policy will add a whole new dimension to the available research.

There is scope for a new endeavor that documents management research within the public sector in China. This may be seen as a sister journal for “Chinese Management Studies” that focuses on the other, much larger Chinese sector, that is, governmental organizations.

This paper documents the emergence of the necessity for a new journal about management in China.

The purpose of this paper is to link literature on China’s real estate sector and the impact of governance, ownership and political connectedness on firm financial performance. Whether these factors impact listed real estate firms differently to firms in other industry sectors is identified.

The paper uses pooled 2008-2013 data on A-share firms. Tobin’s Q captures firm financial performance. Explanatory variables include corporate governance, ownership, local government political connectedness, accounting data and ultimate control. Two-way interactions are estimated between real estate and ownership, governance, political connectedness and other variables. Three-way interactions are estimated between real estate, ownership, control and political connectedness. Year and industry fixed effects are absorbed.

Industry concentration and proportion of state ownership appear to positively impact performance. Firm size, gearing and greater foreign ownership appear to negatively impact performance. However, differences are identified for real estate firms, in which state control and gearing positively impact performance. Greater state and foreign ownership as well as supervisory board size negatively impact performance. Finally, state control in the presence of local government connections negatively impacts performance, while greater state ownership in the presence of local government connections positively impacts performance.

A lack of empirical evidence on the impact of corporate governance, ownership structures and political connectedness on firm performance in China’s real estate sector is addressed. Importantly, relationships among these factors and the financial performance of China’s listed real estate firms differ to those of firms in other industries.

Visual simultaneous localization and mapping (SLAM) has limitations such as sensitivity to lighting changes and lower measurement accuracy. The effective fusion of information from multiple modalities to address these limitations has emerged as a key research focus. This study aims to provide a comprehensive review of the development of vision-based SLAM (including visual SLAM) for navigation and pose estimation, with a specific focus on techniques for integrating multiple modalities.

This paper initially introduces the mathematical models and framework development of visual SLAM. Subsequently, this paper presents various methods for improving accuracy in visual SLAM by fusing different spatial and semantic features. This paper also examines the research advancements in vision-based SLAM with respect to multi-sensor fusion in both loosely coupled and tightly coupled approaches. Finally, this paper analyzes the limitations of current vision-based SLAM and provides predictions for future advancements.

The combination of vision-based SLAM and deep learning has significant potential for development. There are advantages and disadvantages to both loosely coupled and tightly coupled approaches in multi-sensor fusion, and the most suitable algorithm should be chosen based on the specific application scenario. In the future, vision-based SLAM is evolving toward better addressing challenges such as resource-limited platforms and long-term mapping.

This review introduces the development of vision-based SLAM and focuses on the advancements in multimodal fusion. It allows readers to quickly understand the progress and current status of research in this field.

Purpose: The insurance business is confronted with coordination difficulties that necessitate a high level of mobility, flexibility, and the capacity to analyse heterogeneous, location-dependent data from different sources and qualities. Recent innovations in emerging technologies have given the insurance industry new organisational options. When coupled with data analytics, crowdsourcing in the insurance industry facilitates solving complex issues with the wisdom of crowds. The notion of incorporating crowdsourcing and big data into the mainstream activities of insurance management is developed in this article, as are the ramifications and gains of collective intelligence achieved by Crowdsourcing and the added value of crowdsourcing insurance activities.

Design/methodology/approach: This chapter is a conceptual work that builds on relevant literature.

Findings: This chapter analyses what insurance industry managers should consider when coordinating crowdsourced activities and how they may benefit from collective intelligence combined with data analytics in terms of efficient and real-time response management for the insurance industry. Furthermore, it is demonstrated how they may use crowdsourcing to exploit information and benefit from invoking additional resources and eliminating the institutional voids present in the industry.

Practical implications: Exemplary applications that take advantage of crowdsourcing and data analytics would help the insurance sector respond flexibly, efficiently, and effectively in real time.

Originality/value: This chapter offers new collaborative ways to enhance the decision-making of insurance industry managers. The relevance of overcoming institutional voids is expanded, and repercussions from the given framework are suggested using data analytics.