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The purpose of this paper is to develop a control strategy for human–robot collaborative manipulation tasks that can deal with proximity signals from 373 interconnected cells of an artificial skin.

The robot and the operator accomplish an industrial task while interacting in a shared workspace. The robot controller detects and avoids collisions based on the information from the artificial skin. Conflicting constraints can be handled by prioritizing between hard and soft constraints or by weighing the different constraints.

Weak soft constraints (low weight) are specified to command the robot to move along a nominal path with constant velocity. Stronger soft constraints (higher weight) prevent collisions by means of either moving the end effector backward along the path or circumventing an obstacle. The proposed approach is validated experimentally.

As a first contribution, this paper proposes a discrete optimization algorithm activates an a priori selected maximum number of cells. The algorithm selects the appropriate distribution based on the amplitude of each signal and the spatial distribution of the proximity measurements. A second contribution is the specification of a human–robot collaborative application as an optimization problem using eTaSL (expression graph-based task specification language), which provides reactive control.

This paper aims to report a flexible position-sensitive sensor that can be applied as large-area electronic skin over the stiff media.

The sensor uses a whole piezoresistive film as a touch sensing area. By alternately constructing two uniform electric fields with orthogonal directions in the piezoresistive film, the local changes in conductivity caused by touch can be projected to the boundary along the equipotential line under the constraint of electric field. Based on the change of boundary potential in the two uniform electric fields, it can be easy to determine the position of the contact area in the piezoresistive film.

Experiment results show the proposed tactile sensor is capable of detecting the contact position and classifying the contact force in real-time based on the changes of the potential differences on the boundary of the sensor.

The application example of using the sensor sample as a controller in shooting game is presented in this paper. It shows that the sensor has excellent touch sensing performance.

In this paper, a position-sensitive electronic skin is proposed. The experiment results show that the sensor has great application prospects in the field of interactive tactile sensing.

This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused.

Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose.

LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction.

The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing.

Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely.

LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace.

This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.

The aim of this paper is to investigate implementations of carbon‐black filled silicone rubber for tactile sensation.

The sensor‐elements for this tactile sensing structure were made by press‐curing from carbon‐black filled silicone rubber.

The behaviour of the silicone rubber shows strong non‐linearity, therefore, the sensor cannot be used for accurate measurements. The greatest advantage of this material lies in its high elasticity.

A new method for artificial tactile sensing skin for robotic applications.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

This paper aims to provide details of recent advances in robotic prostheses with the emphasis on the control and sensing technologies.

Following a short introduction, this paper first discusses the main robotic prosthesis control strategies. It then provides details of recent research and developments using non-invasive and invasive brain–computer interfaces (BCIs). These are followed by examples of studies that seek to confer robotic prostheses with sensory feedback. Finally, brief conclusions are drawn.

A significant body of research is underway involving electromyographic and BCI technologies, often in combination with advanced data processing and analysis schemes. This has the potential to yield robotic prostheses with advanced capabilities such as greater dexterity and sensory feedback.

This illustrates how electromyographic, BCI, signal processing and sensor technologies are being used to create robotic prostheses with enhanced functionality.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.

Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.

Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.

Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.

This paper aims to provide details of recent developments in robotic tactile sensing.

Following a short introduction, this paper first provides an overview of tactile sensing effects and technologies. It then discusses recent developments in tactile sensing skins. Tactile sensing for robotic prosthetics and hands is then considered and is followed by a discussion of “tactile intelligence”. Various experimental results are included. Finally, brief concluding comments are drawn.

This shows that many advanced, sensitive and technologically varied tactile sensing devices are being developed. These devices are expected to impart robots with a range of enhanced capabilities such as improved gripping and manipulation, object recognition, the control and robotic hands and prosthetics and collision detection.

Tactile sensing has an increasingly important role to play in robotics, and this paper provides a technical insight into a number of recent developments and their applications.

This study aims to provide an insight into the role of robots in the entertainment industry.

Following a short introduction, this study first considers applications in amusement parks and robotic rides and highlights some current development activities. It then discusses the roles of robots in film making. This is followed by a consideration of the role of humanoid robots and applications in the performing arts and includes details of some recent research. Finally, brief conclusions are drawn.

This study shows that robots are used in many sectors of the entertainment industry. These include applications in amusement parks which will expand due to technological innovations; camera control and the creation of special effects in film making; and all manner of existing and emerging applications in the performing arts, including dance, music and opera, where humanoid robots play a key role. Several fully robotic rock bands have been developed and recent research has shown that artificial intelligence techniques can allow robots to compose as well as play music.

This study shows the growing importance of robots in the entertainment industry by providing details of a selection of applications.