A motivational model based on artificial biological functions for the intelligent decision-making of social robots

Modelling the biology behind animal behaviour has attracted great interest in recent years. Nevertheless, neuroscience and artificial intelligence face the challenge of representing and emulating animal behaviour in robots. Consequently, this paper presents a biologically inspired motivational model to control the biological functions of autonomous robots that interact with and emulate human behaviour. The model is intended to produce fully autonomous, natural, and behaviour that can adapt to both familiar and unexpected situations in human–robot interactions. The primary contribution of this paper is to present novel methods for modelling the robot’s internal state to generate deliberative and reactive behaviour, how it perceives and evaluates the stimuli from the environment, and the role of emotional responses. Our architecture emulates essential animal biological functions such as neuroendocrine responses, circadian and ultradian rhythms, motivation, and affection, to generate biologically inspired behaviour in social robots. Neuroendocrinal substances control biological functions such as sleep, wakefulness, and emotion. Deficits in these processes regulate the robot’s motivational and affective states, significantly influencing the robot’s decision-making and, therefore, its behaviour. We evaluated the model by observing the long-term behaviour of the social robot Mini while interacting with people. The experiment assessed how the robot’s behaviour varied and evolved depending on its internal variables and external situations, adapting to different conditions. The outcomes show that an autonomous robot with appropriate decision-making can cope with its internal deficits and unexpected situations, controlling its sleep–wake cycle, social behaviour, affective states, and stress, when acting in human–robot interactions.The research leading to these results has received funding from the projects: Robots Sociales para Estimulación Física, Cognitiva y Afectiva de Mayores (ROSES), RTI2018-096338-B-I00, funded by the Ministerio de Ciencia, Innovación y Universidades; Robots sociales para mitigar la soledad y el aislamiento en mayores (SOROLI), PID2021-123941OA-I00, funded by Agencia Estatal de Investigación (AEI), Spanish Ministerio de Ciencia e Innovación. This publication is part of the R&D&I project PLEC2021-007819 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR

Socially Assistive Robots for Exercising Scenarios. Studies on group effects, feedback, embodiment and adaption

Schneider S. Socially Assistive Robots for Exercising Scenarios. Studies on group effects, feedback, embodiment and adaption. Bielefeld: Universität Bielefeld; 2019.Even though positive effects of being physically active are commonly known, only a few parts of the world population are sufficiently ac- tive. The World Health Organization (WHO) states that this problem affects 31% of the adult’s world population and 80% of the adolescent population. Appropriate levels of physical activity (PA) are essential to prevent obesity in childhood and to keep a Quality of Life (QOL) in old age but are also essential to prevent other Noncommunicable Diseases (NCDs). Thus, physical inactivity is growing into a severe problem globally, and there is a growing need to motivate people to become more physically active during their lifetime. One primary cause that raises PA levels is having a peer or help from professionals. However, having assistance is not possible in every situation. It might be challenging to find and schedule with a partner or to commute to other places. Roboticist introduced Socially Assistive Robot (SAR) as an assistive tool for exercising, cognitive or rehabilitation tasks. This thesis explores SAR in the context of exercising along four features that have been partly targeted but not yet thoroughly investigated. These features are a) the social role of the robot, b) encouragement c) embodiment and d) adaptation. First, this thesis looks at the mo- tivational effects of exercising with SAR concerning features a) - c). Second, this thesis questions how a system can adapt to the user, and whether adaptivity or adaptability is enough to close the gap between user needs and system behavior. I conducted studies that test the dif- ferent features by assessing subjective ratings of the robot as well as measurable motivational variables (e.g., time spent exercising with the robot) in a bodyweight workout scenario. The results show that features a) - c) have a positive influence on user’s exercising time. Additionally, users perceive a robot compan- ion as more likable than a robot instructor or a human partner. Fur- thermore, an adaptive robot increases the associated competence and quality of relationship compared to an adaptable robot. However, the results also show that the robot does not always have to exercise along with the user. In situations where it is not possible, the robot could also only give encouraging feedback. This thesis backs up earlier find- ings of using SAR by replicating motivational group exercising ef- fects found in Human-Human Interaction (HHI). Thus, the evidence that SARs are a suitable tool for rehabilitative interventions increases which may convince health experts to consider SAR as a useful thera- peutic tool. Nevertheless, this thesis evaluated the effects only during short-term interactions. Thus, proving that the found effects are long- lasting is essential for future studies

Assist-as-needed EMG-based control strategy for wearable powered assistive devices

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)Robotic-based gait rehabilitation and assistance using Wearable Powered Assistive Devices (WPADs), such as orthosis and exoskeletons, has been growing in the rehabilitation area to recover and augment the motor function of neurologically impaired subjects. These WPADs should provide a personalized assistance, since physical condition and muscular fatigue modify from patient to patient. In this field, electromyography (EMG) signals have been used to control WPADs given their ability to infer the user’s motion intention. However, in cases of motor disability conditions, EMG signals present lower magnitudes when compared to EMG signals under healthy conditions. Thus, the use of WPADs managed by EMG signals may not have potential to provide the assistance that the patient requires. The main goal of this dissertation aims the development of an Assisted-As-Needed (AAN) EMG-based control strategy for a future insertion in a Smart Active Orthotic System (SmartOs). To achieve this goal, the following elements were developed and validated: (i) an EMG system to acquire muscle activity signals from the most relevant muscles during the motion of the ankle joint; (ii) machine learning-based tool for ankle joint torque estimation to serve as reference in the AAN EMG-based control strategy; and (iii) a tool for real EMG-based torque estimation using Tibialis Anterior (TA) and Gastrocnemius Lateralis (GASL) muscles and real ankle joint angles. EMG system showed satisfactory pattern correlations with a commercial system. The reference ankle joint torque was generated based on predicted reference ankle joint kinematics, walking speed information (from 1 to 4 km/h) and anthropometric data (body height from 1.51 m to 1.83 m and body mass from 52.0 kg to 83.7 kg), using five machine learning algorithms: Support Vector Regression (SVR), Random Forest (RF), Multilayer Perceptron (MLP), Long-Short Term Memory (LSTM) and Convolutional Neural Network (CNN). CNN provided the best performance, predicting the reference ankle joint torque with fitting curves ranging from 74.7 to 89.8 % and Normalized Root Mean Square Errors (NRMSEs) between 3.16 and 8.02 %. EMG-based torque estimation beneficiates of a higher number of muscles, since EMG data from TA and GASL are not enough to estimate the real ankle joint torque.A assistência e reabilitação robótica usando dispositivos de assistência ativos vestíveis (WPADs), como ortóteses e exosqueletos, tem crescido na área da reabilitação com o fim de recuperar e aumentar a função motora de sujeitos com alterações neurológicas. Estes dispositivos devem fornecer uma assistência personalizada, uma vez que a condição física e a fadiga muscular variam de paciente para paciente. Nesta área, sinais de eletromiografia (EMG) têm sido usados para controlar WPADs, dada a sua capacidade de inferir a intenção de movimento do utilizador. Contudo, em casos de deficiência motora, os sinais de EMG apresentam menor amplitude quando comparados com sinais de EMG em condições saudáveis e, portanto, o uso de WPADs geridos por sinais de EMG pode não oferecer a assistência que o paciente necessita. O principal objetivo desta dissertação visa o desenvolvimento de uma estratégia de controlo baseada em EMG capaz de fornecer assistência quando necessário, para futura integração num sistema ortótico ativo e inteligente (SmartOs). Para atingir este objetivo foram desenvolvidos e validados os seguintes elementos: (i) sistema de EMG para adquirir sinais de atividade muscular dos músculos mais relevantes no movimento da articulação do tornozelo; (ii) ferramenta de machine learning para estimação do binário da articulação do tornozelo para servir como referência na estratégia de controlo; e (iii) ferramenta de estimação do binário real do tornozelo considerando sinais de EMG dos músculos Tibialis Anterior (TA) e Gastrocnemius Lateralis (GASL) e ângulo real do tornozelo. O sistema de EMG apresentou correlações satisfatórias com um sistema comercial. O binário de referência para o tornozelo foi gerado com base no ângulo de referência da mesma articulação, velocidade de marcha (de 1 até 4 km/h) e dados antropométricos (alturas de 1.51 m até 1.83 e massas de 52.0 kg até 83.7 kg), usando cinco algoritmos de machine learning: Support Vector Machine, Random Forest, Multilayer Perceptron, Long-Short Term Memory e Convolutional Neural Network. CNN apresentou a melhor performance, prevendo binários de referência do tornozelo com um fit entre 74.7 e 89.8 % e Normalized Root Mean Square Errors (NRMSE) entre 3.16 e 8.02 %. A estimativa do torque com base em sinais de EMG requer a inclusão de um maior número de músculos, uma vez que sinais de EMG dos músculos TA e GASL não foram suficientes

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools