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This paper aims to propose a conceptual scale model of mobile drilling robot according to the actual drilling rig and working conditions to improve the safety and automation of drilling in tunnel construction and coal mining applications.

A couple of pinion and rack serves as the support mechanism driven by a motor with low rotation speed at high power, and these components are assembled in the center of the robot to tightly fasten the whole body together. The drilling rod and the sleeve are connected through a hole with screw thread so that the rod feeds and rotates simultaneously along with the sleeve. The robot model is automatically controlled by a single-chip microcomputer, and the anti-disturbance circuit is designed as well. A five-step rule obstacle avoidance method is proposed to ensure safe and reliable movement.

The results of simulation experiments on drilling operation do indicate that the mechanism and control method are feasible and effective.

The robot is nearly complete but indeed remains only an experimental machine.

The design of the mechanism structure for the conceptual robot is novelty. The method of five-step rule obstacle avoidance can improve reliability of obstacle avoidance according to the experimental results, which can meet the requirements of complex working conditions underground coal mine.

Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.

This paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.

The empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.

This paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.

The acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

In the process of robot shell design, it is necessary to match the shape of the input 3D original character mesh model and robot endoskeleton, in order to make the input model fit for robot and avoid collision. So, the purpose of this paper is to find an object of reference, which can be used for the process of shape matching.

In this work, the authors propose an interior bounded box (IBB) approach that derives from oriented bounding box (OBB). This kind of box is inside the closed mesh model. At the same time, it has maximum volume which is aligned with the object axis but is enclosed by all the mesh vertices. Based on the IBB of input mesh model and the OBB of robot endoskeleton, the authors can complete the process of shape matching. In this paper, the authors use an evolutionary algorithm, covariance matrix adaptation evolution strategy (CMA-ES), to approximate the IBB based on skeleton and symmetry of input character mesh model.

Based on the evolutionary algorithm CMA-ES, the optimal position and scale information of IBB can be found. The authors can obtain satisfactory IBB result after this optimization process. The output IBB has maximum volume and is enveloped by the input character mesh model as well.

To the best knowledge of the authors, the IBB is first proposed and used in the field of robot shell design. Taking advantage of the IBB, people can quickly obtain a shell model that fit for robot. At the same time, it can avoid collision between shell model and the robot endoskeleton.

This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.

The purpose of this study is to discover and model the asymmetry in the price volatility of financial markets, in particular the foreign exchange markets as the first underlying applications.

The volatility of the financial market price is usually defined with the standard deviation or variance of the price or price returns. This standard definition of volatility is split into the upper part and the lower one, which are termed here as Yang volatility and Yin volatility. However, the definition of yin‐yang volatility depends on the scale of the time, thus the notion of scale space of price‐time is also introduced.

It turns out that the duality of yin‐yang volatility expresses not only the asymmetry of price volatility, but also the information about the trend. The yin‐yang volatilities in the scale space of price‐time provide a complete representation of the information about the multi‐level trends and asymmetric volatilities. Such a representation is useful for designing strategies in market risk management and technical trading. A trading robot (a complete automated trading system) was developed using yin‐yang volatility, its performance is shown to be non‐trivial. The notion and model of yin‐yang volatility has opened up new possibilities to rewrite the option pricing formulas, the GARCH models, as well as to develop new comprehensive models for foreign exchange markets.

The asymmetry of price volatility and the magnitude of volatility in the scale space of price‐time has yet to be united in a more coherent model.

The new model of yin‐yang volatility and scale space of price‐time provides a new theoretical structure for financial market risk. It is likely to enable a new generation of core technologies for market risk management and technical trading strategies.

This work is original. The new notion and model of yin‐yang volatility in scale space of price‐time has cracked up the core structure of the financial market risk. It is likely to open up new possibilities such as: a new portfolio theory with a new objective function to minimize the sum of the absolute yin‐volatilities of the asset returns, a new option pricing theory using yin‐yang volatility to replace the symmetric volatility, a new GARCH model aiming to model the dynamics of yin‐yang volatility instead of the symmetric volatility, new technical trading strategies as are shown in the paper.

Driven by sustainable production, mobile robots are introduced as a new clean-energy material handling tool for mixed-model assembly lines (MMALs), which reduces energy consumption and lineside inventory of workstations (LSI). Nevertheless, the previous part feeding scheduling method was designed for conventional material handling tools without considering the flexible spatial layout of the robotic mobile fulfillment system (RMFS). To fill this gap, this paper focuses on a greening mobile robot part feeding scheduling problem with Just-In-Time (JIT) considerations, where the layout and number of pods can be adjusted.

A novel hybrid-load pod (HL-pod) and mobile robot are proposed to carry out part feeding tasks between material supermarkets and assembly lines. A bi-objective mixed-integer programming model is formulated to minimize both total energy consumption and LSI, aligning with environmental and sustainable JIT goals. Due to the NP-hard nature of the proposed problem, a chaotic differential evolution algorithm for multi-objective optimization based on iterated local search (CDEMIL) algorithm is presented. The effectiveness of the proposed algorithm is verified by dealing with the HL-pod-based greening part feeding scheduling problem in different problem scales and compared to two benchmark algorithms. Managerial insights analyses are conducted to implement the HL-pod strategy.

The CDEMIL algorithm's ability to produce Pareto fronts for different problem scales confirms its effectiveness and feasibility. Computational results show that the proposed algorithm outperforms the other two compared algorithms regarding solution quality and convergence speed. Additionally, the results indicate that the HL-pod performs better than adopting a single type of pod.

This study proposes an innovative solution to the scheduling problem for efficient JIT part feeding using RMFS and HL-pods in automobile MMALs. It considers both the layout and number of pods, ensuring a sustainable and environmental-friendly approach to production.

While robots have increasingly threatened frontline employees’ (FLEs) future employment by taking over more mechanical and analytical intelligence tasks, they are still unable to “experience” and “feel” to occupy empathetic intelligence tasks that can be handled better by FLEs. This study, therefore, aims to empirically develop and validate a scale measuring the new so-called empathetic creativity as being creative in practicing and performing empathetically intelligent skills during service encounters.

This study adopts a multistage design to develop the scale. Phase 1 combines a literature review with text mining from 3,737 service robots-related YouTube comments to generate 16 items capturing this new construct. Phase 2 assesses both face and content validity of those items, while Phase 3 recruits Prolific FLEs sample to evaluate construct validity. Phase 4 checks this construct’s nomological validity using PLS-SEM and Phase 5 experiments dedicated effort (vs natural talent) as an effective approach to foster FLEs’ perceived empathetic creativity.

The final scale is comprised of 13 refined items that capture three dimensions (social, interactive and emotional) of empathetic creativity. This research provides timely implications to help FLEs in high-contact services stay competitive.

This study introduces the new construct of empathetic creativity, which goes beyond the traditional definition of creativity in services and highlights the importance of empathetic intelligence for FLEs in future employment. This study also develops a multi-item scale to measure this construct, which can be applied to future service management research.

This paper aims to present a new friction-stir-weld robot for large-scale complex surface structures, which has high stiffness and good flexibility.

The robot system is designed according to manufacturability of large aluminum products in aeronautic and astronautic area. The kinematic model of the robot is established, and a welding trajectory planning method is also developed and verified by experiments.

Experimental results show that the robot system can meet the requirements of friction stir welding (FSW) for large-scale complex surface structures.

Compared with other heavy robotic arm and machine tool welding devices, this robot has better working quality and capability, which can greatly improve the manufacturability for large-scale complex surface structures.

The friction-stir-weld robot system is a novel solution for welding large-scale complex surface structures. Its major advantages are the high stiffness, good flexibility and high precision of the robot body, which can meet the requirements of FSW. Besides, a welding trajectory planning method based on iterative closest point (ICP) algorithm is used for welding trajectory.

The purpose of this paper is to estimate the required number of robots consisting of some non-repairable components, by employing a renewal model. Considering the importance of the availability of standby autonomous robots for reducing and preventing down-times of advanced production systems, which imposes a considerable loss, the present research tries to introduce a practical model for the determination of the required number of autonomous robots.

Most of the available research on the estimation of the required standby components based on the reliability characteristics of components has not considered the environmental factors influencing the reliability characteristics. Therefore, such estimations are not accurate enough. In contrast, this paper focuses on the influence of the environmental and human factors (e.g. the operators’ skill) on the robot reliability characteristics.

A model based on the Weibull renewal process combined with the cold standby strategy is developed for reliability evaluation of the system. The effectiveness of the proposed integrated reliability evaluation model is worked out in some cases.

Determining a required number of robots is an important issue in availability and utilization of a complex robotic production system. In an advanced production system, while the estimation process of a required number of robots can be performed through different approaches, one of the realistic estimation methods is based on the system’s reliability that takes into consideration the system operating environment. To forecast the required number of robots for an existing production system, in some cases, the assumption of a constant failure rate does not differ much from the assumption of a non-constant failure rate and can be made with an acceptable error.

In an industrial robotic cell, the optimal layout planning problem needs critical analysis, as it indirectly affects the manufacturing time and cost involved in the production process. This paper aims to propose a generic three-step robotic cell layout planning method and aims to enhance the adaptability of robotic manufacturing cell in small-scale industries.

The method uses the data generated from the point cloud modeling and simulation of the objects (machines and robot) to optimize their positions and orientations in the cell. The simulated annealing algorithm has been used to solve the optimization problem with minimum joint displacement criterion. This approach is critically analyzed and discussed against the data collected from an industrial robotic cell in a foundry shop of a pipe manufacturing industry.

More than 50 per cent reduction in the net joint movement of the robot has been achieved. Immediate feedback of the results by a three-dimensional view of the optimal cell layout without using any commercial robotic simulation package.

The layout optimization of an industrial robotic cell based on the point cloud modeling of its objects is the novelty of the method.