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The purpose of this paper is to propose a method to avoid hyperstaticity and eventually reduce the magnitude of undesired force/torques. The authors also study the influence of hyperstaticity on human motor control during a redundant task.

Increasing the level of transparency of robotic interfaces is critical to haptic investigations and applications. This issue is particularly important to robotic structures that mimic the human counterpart's morphology and attach directly to the limb. Problems arise for complex joints such as the wrist, which cannot be accurately matched with a traditional mechanical joint. In such cases, mechanical differences between human and robotic joint cause hyperstaticity (i.e. over-constrained) which, coupled with kinematic misalignment, leads to uncontrolled force/torque at the joint. This paper focusses on the prono-supination (PS) degree of freedom of the forearm. The overall force and torque in the wrist PS rotation is quantified by means of a wrist robot.

A practical solution to avoid hyperstaticity and reduce the level of undesired force/torque in the wrist is presented. This technique is shown to reduce 75 percent of the force and 68 percent of the torque. It is also shown an over-constrained mechanism could alter human motor strategies.

The presented solution could be taken into account in the early phase of design of robots. It could also be applied to modify the fixation points of commercial robots in order to reduce the magnitude of reaction forces and avoid changes in motor strategy during the robotic therapy.

In this paper for the first time the authors study the effect of hyperstaticity on both reaction forces and human motor strategies.

The purpose of this paper is to describe the development of a device to support rehabilitation of a patient's upper limb motion.

The device has five degrees of freedom by virtue of its link mechanism. It consists of Joints 1‐5. Apparatus for use in so‐called welfare applications, such as this device, must be safe, flexible, and lightweight. A pneumatic cylinder, arranged and integrated with the device, was used to operate it. The device has two rehabilitation modes corresponding to different rehabilitation contents. The first mode is the muscular recovery and movable region expansion mode (Mode A). The second mode is a practical function recovery mode (Mode B). A compliance control and a position control system are applied for those modes.

By arranging the pneumatic cylinder optimally, results show that the device has compact and wide operating range and compliance‐control performance for Mode A. Position‐control performance for Mode B was verified experimentally. Moreover, the paper evaluates the effectiveness of the device and its control system through electromyography, which confirms that the developed device can support a patient's rehabilitation training.

The device has a simple link mechanism and an attached pneumatic cylinder, thereby constituting a lightweight and compact mechanism. The device has two rehabilitation modes corresponding to different rehabilitation contents. Using the device, a patient can conduct muscular power recovery training, movable region expansion training, and upper limb practical function recovery training.

The purpose of this paper is to propose a variable impedance control method of finger exoskeleton for hand rehabilitation using the contact forces between the finger and the exoskeleton, making the output trajectory of finger exoskeleton comply with the natural flexion-extension (NFE) trajectory accurately and adaptively.

This paper presents a variable impedance control method based on fuzzy neural network (FNN). The impedance control system sets the contact forces and joint angles collected by sensors as input. Then it uses the offline-trained FNN system to acquire the impedance parameters in real time, thus realizing tracking the NFE trajectory. K-means clustering method is applied to construct FNN, which can obtain the number of fuzzy rules automatically.

The results of simulations and experiments both show that the finger exoskeleton has an accurate output trajectory and an adaptive performance on three subjects with different physiological parameters. The variable impedance control system can drive the finger exoskeleton to comply with the NFE trajectory accurately and adaptively using the continuously changing contact forces.

The finger is regarded as a part of the control system to get the contact forces between finger and exoskeleton, and the impedance parameters can be updated in real time to make the output trajectory comply with the NFE trajectory accurately and adaptively during the rehabilitation.

Describes recent developments at the Tokyo bi‐annual International Robot Exhibition. More exhibitors were present than in previous years, however very few new innovative technologies /products were observed. In the middle of the depressed economy Japanese industrial robot manufacturers are struggling to reduce cost, reshuffle business structure and try everything to survive. A total solution approach and strategic alliances were evident. On the other hand there is a sign of emerging non‐manufacturing market, especially in the entertainment area.

The following article is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot journal as a method 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 paper aims to discuss these issues.

The interviewee is Jacob Rosen, a Professor of Medical Robotics at the Department of Mechanical and Aerospace Engineering, University of California, Los Angeles (UCLA), where he directs the Bionics Lab. Professor Rosen is also the Director of Surgical Robotics Engineering at the UCLA School of Medicine’s Center for Advanced Surgical and Interventional Technology and has joint appointments at UCLA’s Department of Surgery and UCLA’s Department of Bioengineering. Professor Rosen is the co-founder of the companies Applied Dexterity, ExoSense and SPI. As a pioneer in medical robotics devices and technologies, Professor Rosen describes his unique approaches and philosophies.

Dr Rosen received his BSc degree in Mechanical Engineering, MSc and PhD degrees in Biomedical Engineering from Tel-Aviv University in 1987, 1993 and 1997, respectively. From 1987 to 1992, he served as an officer in the Israeli Defense Forces studying human–machine interfaces. From 1993 to 1997, he was a research associate at Tel-Aviv University, as well as held a position at a startup company developing innovative orthopedic spine/pelvis implants. From 2001-2013, he held faculty positions at the University of Washington and at University of California, Santa Cruz.

Dr Rosen developed several key systems in the field of medical robotics, such as the Blue and the Red Dragon, for minimally invasive surgical skill evaluation; RAVEN, a surgical robotic system for telesurgery; and several generations of upper and lower limb exoskeletons including the Exo-UL7 – a dual arm wearable robotic system. He is a co-author of 100 manuscripts in the field of medical robotics and a co-author and co-editor of two books entitled “Surgical Robotics – Systems, Applications, and Visions” and “Redundancy in Robot Manipulators and Multi-robot systems” published by Springer. Professor Rosen has filed eight different patent applications and also works as an expert witness and consultant on design, patent protection & litigation and malpractice regarding surgical robotics.

Fully-actuated unmanned aerial vehicles (UAVs) are a growing and promising field of research, which shows advantages for aerial physical interaction. The purpose of this paper is to construct a force sensor-denied control method for a fully-actuated hexarotor to conduct aerial interaction with accurate force exerted outward.

First, by extending single-dimension impedance model to the fully-actuated UAV model, an impedance controller is designed for compliant UAV pose/force control. Then, to estimate the interaction force between UAV end-effector and external environment accurately, combined with super-twisting theory, a nonlinear force observer is constructed. Finally, based on impedance controller and estimated force from observer, an interaction force regulation method is proposed.

The presented nonlinear observer-based impedance control approach is validated in both simulation and environments, in which the authors try to use a fully-actuated hexarotor to accomplish the task of aerial physical interaction finding that a specified force is able to be exerted to environment without any information from force sensors.

A solution of aerial physical interaction for UAV system enabling accurate force exerted outward without any force sensors is proposed in this paper.

The purpose of this paper is to make compliant training control of exoskeleton for ankle joint with electromyograph (EMG)-torque interface.

A virtual compliant mapping which is modeled by mass-spring-damper system is incorporated into the whole system at the reference input. The EMG-torque interface contains both data acquisition and torque estimator/predictor, and extreme learning machine is utilized for joint torque estimation/prediction from multiple channels of EMG signals.

The reference ankle joint angle to follow is produced from the compliance mapping whose input is the measured/predicted torque on healthy subjects. The control system works well with the desired angle to track. In the actuation level, the input torque to drive the ankle exoskeleton is less than the actual torque of the subject(s). This may have positive influence on diminishing overshoot of input torque from motors and protect the actuators. The torque prediction and final tracking control performance demonstrate the efficiency of the presented architecture.

This work can be beneficial to compliant training of ankle exoskeleton system for pilots and enhance current training control module in rehabilitation.

Multi-sensor fusion in robotic dexterous hands is a hot research field. However, there is little research on multi-sensor fusion rules. This study aims to introduce a multi-sensor fusion algorithm using a motor force sensor, film pressure sensor, temperature sensor and angle sensor, which can form a consistent interpretation of grasp stability by sensor fusion without multi-dimensional force/torque sensors.

This algorithm is based on the three-finger force balance theorem, which provides a judgment method for the unknown force direction. Moreover, the Monte Carlo method calculates the grasping ability and judges the grasping stability under a certain confidence interval using probability and statistics. Based on three fingers, the situation of four- and five-fingered dexterous hand has been expanded. Moreover, an experimental platform was built using dexterous hands, and a grasping experiment was conducted to confirm the proposed algorithm. The grasping experiment uses three fingers and five fingers to grasp different objects, use the introduced method to judge the grasping stability and calculate the accuracy of the judgment according to the actual grasping situation.

The multi-sensor fusion algorithms are universal and can perform multi-sensor fusion for multi-finger rigid, flexible and rigid-soft coupled dexterous hands. The three-finger balance theorem and Monte Carlo method can better replace the discrimination method using multi-dimensional force/torque sensors.

A new multi-sensor fusion algorithm is proposed and verified. According to the experiments, the accuracy of grasping judgment is more than 85%, which proves that the method is feasible.

Purpose: This paper presents a review of the current state and potential capabilities for application of robots, artificial intelligence and automated services (RAISA) in hotel companies.

Design/methodology/approach: A two-step approach was applied in this study. First, the authors make a theoretical overview of the robots, artificial intelligence and service automation (RAISA) in hotels. Second, the authors make a detailed overview of various case studies from global hotel practice.

Findings: The application of RAISA in hotel companies is examined in connection with the impact that technology has on guest experience during each of the five stages of the guest cycle: pre-arrival, arrival, stay, departure, assessment.

Research implications: Its implications can be searched with respect to future research. It deals with topics such as how different generations (guests and employees) perceive RAISA in the hotel industry and what is the attitude of guests in different categories of hotels (luxury and economy) towards the use of RAISA. It also shows what is the attitude of different types of tourists (holiday, business, health, cultural, etc.) and what kinds of robots (androids or machines) are more appropriate for different types of hotel operations.

Practical implications: The implications are related to the improvement of operations and operational management, marketing and sales, enhancement of customer experience and service innovation, training and management.

Originality/value: This book chapter complements and expands research on the role of RAISA in the hotel industry and makes some projections about the use of technologies in the future.