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To ensure the motion attitude and stable contact force of massage robot working on unknown human tissue environment, this study aims to propose a robotic system for autonomous massage path planning and stable interaction control.

First, back region extraction and acupoint recognition based on deep learning is proposed, which provides a basis for determining the working area and path points of the robot. Second, to realize the standard approach and movement trajectory of the expert massage, 3D reconstruction and path planning of the massage area are performed, and normal vectors are calculated to control the normal orientation of robot-end. Finally, to cope with the soft and hard changes of human tissue state and body movement, an adaptive force tracking control strategy is presented to compensate the uncertainty of environmental position and tissue hardness online.

Improved network model can accomplish the acupoint recognition task with a large accuracy and integrate the point cloud to generate massage trajectories adapted to the shape of the human body. Experimental results show that the adaptive force tracking control can obtain a relatively smooth force, and the error is basically within ± 0.2 N during the online experiment.

This paper incorporates deep learning, 3D reconstruction and impedance control, the robot can understand the shape features of the massage area and adapt its planning massage path to carry out a stable and safe force tracking control during dynamic robot–human contact.

As Chinese massage is increasingly popular, many physicians are needed these days. In order to promote the experience and skills of experts and reduce labour intensity during massage, a massage robot, which could reproduce the expert techniques with individualized manipulation parameters and enhanced safety control strategies, is presented in this paper.

The kinematic and force features of key massage techniques, such as Thumb Kneading, Pressing, Rolling, Vibrating and Pinching, are summarized by analyzing the massage processes of expert physicians, and a mathematical model for robotic massage is established. With safety issues taken into account, the overall system structure of the massage robot is proposed. The system generally consists of a positioning platform and a massage end‐effector which implements the massage techniques, and the end‐effector is further divided into a parallel mechanism and a massage hand to accommodate different techniques. Visual tracking is used for positioning acupuncture points by recognizing markers on a massage vest worn by the patient. A pain threshold value is introduced to individualize therapy schemes and a force‐position control method based on the pain threshold is presented.

VAS (Visual Analogue Scale) tests for lumbar muscle strain are carried out using the massage robot, and the treatment effect of the massage robot based on traditional Chinese massage therapy theory is initially validated.

The treatment effect of the massage robot needs to be assessed clinically for more occasions and more clinical experiments will be conducted, to optimize the configuration and control strategy to meet the clinical needs in future work.

The robotic massage system presented in this paper is acting on acupuncture points based on traditional Chinese massage therapy theory, with human manipulation techniques reproduced and expert experiences incorporated. The massage robot can take the place of a massager to perform Chinese massage. Most of the massage robotic systems published in the world perform only one massage technique and the whole massage process is not completely considered. By comparison, the authors' massage robot could perform five techniques. Furthermore, the authors have designed the procedure of robotic massage specifically for patients who suffer from lumbar muscle strain.

To ensure accurate position and force control of massage robot working on human body with unknown skin characteristics, this study aims to propose a novel intelligent impedance control system.

First, a skin dynamic model (SDM) is introduced to describe force-deformation on the human body as feed-forward for force control. Then a particle swarm optimization (PSO) method combined with graph-based knowledge transfer learning (GKT) is studied, which will effectively identify personalized skin parameters. Finally, a self-tuning impedance control strategy is designed to accommodate uncertainty of skin dynamics, system delay and signal noise exist in practical applications.

Compared with traditional least square method, genetic algorithm and other kinds of PSO methods, combination of PSO and GKT is validated using experimental data to improve the accuracy and convergence of identification results. The force control is effective, although there are contour errors, control delay and noise problems when the robot does massage on human body.

Integrating GKT into PSO identification algorithm, and designing an adaptive impedance control algorithm. As a result, the robot can understand textural and biological attributes of its surroundings and adapt its planning activities to carry out a stable and accurate force tracking control during dynamic contacts between a robot and a human.

Purpose: The purpose of this chapter is to elaborate on the major conceptual and practical considerations of the use of robots, artificial intelligence and service automation (RAISA) in travel, tourism, and hospitality companies (TTH).

Design/methodology/approach: The chapter develops a conceptual framework of the major issues related to the use of RAISA in the travel, tourism and hospitality context.

Findings: The findings indicate that while there is a creeping incursion of RAISA into TTH, there are major concerns that the TTH industry has to consider in regard to automating TTH services.

Practical implications: In a practical sense, the chapter identifies the decisions that TTH industry professionals need to take when dealing with RAISA technologies. Furthermore, the chapter elaborates on the impacts RAISA have on business operations, marketing management, human resources and financial management of TTH companies. The TTH industry has to adjust its practices and communicate with its workforce in ways as not to increase Luddite tendencies and resistance among employees.

Social implications: The analysis shows that there is an upcoming era in which automation of services will be so advanced that wealthy countries may not need to import labour to make up with its own aging workforce, suggesting that RAISA and its further development has the potential for disrupting society and international relations.

Originality/value: This chapter provides a comprehensive review of the issues related to the use of RAISA in the TTH industry, including the drivers of RAISA adoption in tourism, advantages and disadvantages of RAISA technologies compared to human employees, decisions that managers need to take, and the impacts of RAISA on business processes. It shows how macroenvironmental pressures shape the microeconomic decisions to use RAISA in a TTH context.

The purpose of this study is to examine how consumers perceive the importance of using robot technologies for 12 services evaluated under two categories considering the technology acceptance model (TAM).

The conceptual model analysis used structural equation modeling with the partial least squares estimation method, considering 638 responses.

The results revealed that the perceived importance (PI) of robotic service delivery tasks under “room division” and “food and beverage and secondary services” affect perceived usefulness (PU) and perceived ease of use (PEOU) differently. Besides, PEOU and PU significantly influence attitudes toward using robot-staffed hotels.

The nonprobability convenience sampling method was used as the data collection method. Future studies that prefer probabilistic methods will open a different perspective for evaluating the results.

This study’s empirical findings reveal which robot-delivered services are found significant by the customers and contribute to increased customer satisfaction and loyalty. In addition, it guides accurate demand and investment planning for the tourism and hospitality industry in the post-COVID-19 era.

To the best of the authors’ knowledge, previous literature has not tested or confirmed the effects of PI related to two groups of robotic service delivery tasks on utilitarian variables. This study contributes to the literature by examining how different robotic service delivery tasks are linked to the TAM framework in a hotel setting.

酒店不同类型服务机器人的使用对客人入住意愿的影响

本研究以技术接受模型 (TAM)为理论, 考察了消费者如何看待使用机器人技术的两个类别下评估的十二项服务的重要性。

本研究使用概念模型分析和具有偏最小二乘估计方法的结构方程建模, 考虑了 638 个响应。

“房间划分”和“餐饮和二级服务”下机器人服务交付任务的感知重要性对感知有用性（PU）和感知易用性（PEOU）的影响不同。此外, PEOU 和 PU 显着影响使用机器人酒店的态度。

本研究采用非概率便利抽样方法作为数据收集方法。本文为未来更偏好概率方法的研究将为评估结果开辟不同的视角。

本研究的实证结果揭示了客户认为重要的机器人提供服务, 并有助于提高客户满意度和忠诚度。此外, 研究结果还有助于指导后 Covid-19 时代旅游和酒店业的准确需求和投资规划。

据我们所知, 以前的文献尚未测试或证实与两组机器人服务交付任务相关的感知重要性对功用性变量的影响。本研究通过检查不同的机器人服务交付任务如何与酒店环境中的 TAM 框架相关联, 为文献做出了贡献。

This paper aims to propose a type of T-shaped two-axis force sensor for measuring the forces in x- and z-axes. The developed sensor has a simple structure and can be effectively assembled into compact devices.

A T-shaped plate, with both ends fixed on a base, is used as the substrate of the sensor. Eight strain gauges are placed in the root of the plate or near the sensor head, which can construct two full Wheatstone bridges on the upper and lower surfaces of the plate. When the x- or z-axes forces are applied to the sensor head, different deformation can be generated to the strain gauges. Therefore, the two Wheatstone bridges can be constructed with a different configuration for measuring the forces in x- or z-axes, respectively.

A prototype was designed and constructed and experiments were carried out to test the basic performance of the sensor. It has been verified that the developed sensor could measure the x- and z-axes forces independently with a high resolution of 2.5 and 5 mN, respectively.

Only one thin plate was used in the design, the forces in x- and z-axes could be measured independently and simultaneously, which made the sensor with a simple structure and compact size. Experiments were also verified that there was no crosstalk error occurred in one axis when the force was applied to the other axis.

The purpose of this paper is to design and develop a new robotic device for the rehabilitation of the upper limbs. The authors are focusing on a new symmetrical robot which can be used to rehabilitate the right upper limb and the left upper limb. The robotic arm can be automatically extended or reduced depending on the measurements of the patient's arm. The main idea is to integrate electrical stimulation into motor rehabilitation by robot. The goal is to provide automatic electrical stimulation based on muscle status during the rehabilitation process.

The developed robotic arm can be automatically extended or reduced depending on the measurements of the patient's arm. The system merges two rehabilitation strategies: motor rehabilitation and electrical stimulation. The goal is to take the advantages of both approaches. Electrical stimulation is often used for building muscle through endurance, resistance and strength exercises. However, in the proposed approach the electrical stimulation is used for recovery, relaxation and pain relief. In addition, the device includes an electromyography (EMG) muscle sensor that records muscle activity in real time. The control architecture provides the ability to automatically activate the appropriate stimulation mode based on the acquired EMG signal. The system software provides two modes for stimulation activation: the manual preset mode and the EMG driven mode. The program ensures traceability and provides the ability to issue a patient status monitoring report.

The developed robotic device is symmetrical and reconfigurable. The presented rehabilitation system includes a muscle stimulator associated with the robot to improve the quality of the rehabilitation process. The integration of neuromuscular electrical stimulation into the physical rehabilitation process offers effective rehabilitation sessions for neuromuscular recovery of the upper limb. A laboratory-made stimulator is developed to generate three modes of stimulation: pain relief, massage and relaxation. Through the control software interface, the physiotherapist can set the exercise movement parameters, define the stimulation mode and record the patient training in real time.

There are certain constraints when applying the proposed method, such as the sensitivity of the acquired EMG signals. This involves the use of professional equipment and mainly the implementation of sophisticated algorithms for signal extraction.

Functional electrical stimulation and robot-based motor rehabilitation are the most important technologies applied in post-stroke rehabilitation. The main objective of integrating robots into the rehabilitation process is to compensate for the functions lost in people with physical disabilities. The stimulation technique can be used for recovery, relaxation and drainage and pain relief. In this context, the idea is to integrate electrical stimulation into motor rehabilitation based on a robot to obtain the advantages of the two approaches to further improve the rehabilitation process. The introduction of this type of robot also makes it possible to develop new exciting assistance devices.

The proposed design is symmetrical, reconfigurable and light, covering all the joints of the upper limbs and their movements. In addition, the developed platform is inexpensive and a portable solution based on open source hardware platforms which opens the way to more extensions and developments. Electrical stimulation is often used to improve motor function and restore loss of function. However, the main objective behind the proposed stimulation in this paper is to recover after effort. The novelty of the proposed solution is to integrate the electrical stimulation powered by EMG in robotic rehabilitation.

Aims to project how electroactive polymer will replace conventional electromagnetic motor driven solutions for service and industrial robots.

Presents the ability of electro active polymer to provide higher power density for robot actuation over conventional approaches. Laboratory tests by DARPA compared electroactive polymer with conventional electromagnetic methodologies as well as shape memory alloy and piezo solutions.

Tests by DARPA and SRI International showed significant power density advantages for electroactive polymer artificial muscles (EPAM). Robot prototypes and well as early commercial prototypes developed by Artificial Muscle, Inc. in pumps, valves, and actuators prove superior performance over other actuation solutions.

Introduces a new low cost, low power consumption, light weight, and silent method for actuation for robots and other motion control devices.

This paper, a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal, aims to impart the combined technological, business and personal experience of a prominent, robotic industry engineer-turned entrepreneur regarding the evolution, commercialization and challenges of bringing a technological invention to market.

The interviewee is Dr Esben H. Ostergaard, inventor, co-founder and chief technology officer of Universal Robots. From building his first robot to solve a local industrial problem at the age of four, to building the world’s first collaborative robot company, Dr Ostergaard shares his lifelong ventures as a robot scientist, inventor and entrepreneur.

Dr Ostergaard received degrees in computer science, physics and multimedia at Aarhus University in Denmark, and a PhD in robotics from the University of Southern Denmark. While at Aarhus, Dr Ostergaard pursued his hobby of robot football, and in 1998, his team STATIC became the world champion of the Federation of International Robot-soccer Association (FIRA). Dr Ostergaard held research positions at the University of Southern California (USC) Robotics Labs and at the Advanced Industrial Science and Technology (AIST) in Tsukuba/Tokyo. During the years 2001-2005 as a researcher and assistant professor in robotics and user interfaces at University of Southern Denmark, he created the foundation for a reinvention of the industrial robot. This led him to found Universal Robots in 2005 with two of his research colleagues.

From a young child who played with LEGOs until he got a Commodore 64, Dr Ostergaard has always been interested in robotics. His unique multidisciplinary education and multicultural research experiences helped him to pioneer a new multi-axis, lightweight industrial robot and launch the successful company, Universal Robots, which has grown from its three co-founders to nearly 150 employees, with more than 4,000 collaborative robot applications installed in over 50 countries worldwide. Dr Ostergaard has over 30 patents and has received many awards, including the 2012 IEEE-IFR Invention and Entrepreneurship Award (IERA), the 2013 Japanese Institute Good Design Award, the 2013 Robotics Business Review Game Changer Award and the Ernst & Young Entrepreneur of the Year 2012 in Region Funen.