Special issue on smart interactions in cyber-physical systems: Humans, agents, robots, machines, and sensors

In recent years, there has been increasing interaction between humans and non‐human systems as we move further beyond the industrial age, the information age, and as we move into the fourth‐generation society. The ability to distinguish between human and non‐human capabilities has become more difficult to discern. Given this, it is common that cyber‐physical systems (CPSs) are rapidly integrated with human functionality, and humans have become increasingly dependent on CPSs to perform their daily routines.The constant indicators of a future where human and non‐human CPSs relationships consistently interact and where they allow each other to navigate through a set of non‐trivial goals is an interesting and rich area of research, discovery, and practical work area. The evidence of con- vergence has rapidly gained clarity, demonstrating that we can use complex combinations of sensors, artificial intelli- gence, and data to augment human life and knowledge. To expand the knowledge in this area, we should explain how to model, design, validate, implement, and experiment with these complex systems of interaction, communication, and networking, which will be developed and explored in this special issue. This special issue will include ideas of the future that are relevant for understanding, discerning, and developing the relationship between humans and non‐ human CPSs as well as the practical nature of systems that facilitate the integration between humans, agents, robots, machines, and sensors (HARMS).Fil: Kim, Donghan. Kyung Hee University;Fil: Rodriguez, Sebastian Alberto. Universidad Tecnológica Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Matson, Eric T.. Purdue University; Estados UnidosFil: Kim, Gerard Jounghyun. Korea University

Guest editorial: sensorimotor contingencies for cognitive robotics

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The sensorimotor approach to cognition states, that the key to bring semantics to the world of a robot, requires making the robot learn the relation between the actions that the robot performs and the change it experiences in its sensed data because of those actions. Those relations are called sensorimotor contingencies (SMCs). This special issue presents a variety of recent developments in SMCs with a particular focus on cognitive robotics applications.Peer ReviewedPostprint (author's final draft

Guest Editorial: Social and human aspects of cyber-physical systems

open6siIn the vision of Industry 4.0, the new industrial revolution is a revolution of cyber-physical systems, of which the Internet of Things forms a key foundation that has a great impact on the way people live, and the way businesses are organised. Cyber-physical systems are often considered feedback systems that integrate computation, networking, and physical processes, and more recently with ‘human-in-the-loop’ as one of the key research topics. The advances in social computing have connected human-inthe-loop in cyber-social systems such as Facebook and Twitter, while their social-physical activities are supported by the cyberphysical systems on or near their bodies and in their interconnected environments. Cyber-physical systems become an integral part of social-cyber-physical systems (SCPS) that weave into the sociotechnical fabric of human society. These hybrid systems, exhibiting both continuous (in physical and social spaces) and discrete (in cyberspaces) dynamic behaviour, give rise to not only new opportunities but also new challenges in designing products and services where human and technical aspects are massively intertwined. This Special Issue aims to present state-of-the-art research attempts and results on the topic of SCPS.openopenHu J.; Liang R.-H.; Shih C.-S.; Catala A.; Marcenaro L.; Osawa H.Hu, J.; Liang, R. -H.; Shih, C. -S.; CATALA MALLOFRE, Andreu; Marcenaro, L.; Osawa, H

Peer assessment as collaborative learning

Peer assessment is an important component of a more participatory culture of learning. The articles collected in this special issue constitute a representative kaleidoscope of current research on peer assessment. In this commentary, we argue that research on peer assessment is currently in a stage of adolescence, grappling with the developmental tasks of identity formation and affiliation. Identity formation may be achieved by efforts towards a shared terminology and joint theory building, whereas affiliation may be reached by a more systematic consideration of research in related fields. To reach identity formation and affiliation, preliminary ideas for a cognitively toned, process-related model of peer assessment and links to related research fields, especially to research on collaborative learning, are presented

Constraining the Size Growth of the Task Space with Socially Guided Intrinsic Motivation using Demonstrations

This paper presents an algorithm for learning a highly redundant inverse model in continuous and non-preset environments. Our Socially Guided Intrinsic Motivation by Demonstrations (SGIM-D) algorithm combines the advantages of both social learning and intrinsic motivation, to specialise in a wide range of skills, while lessening its dependence on the teacher. SGIM-D is evaluated on a fishing skill learning experiment.Comment: JCAI Workshop on Agents Learning Interactively from Human Teachers (ALIHT), Barcelona : Spain (2011

Manufacturing system and enterprise management for Industry 4.0: Guest editorial

Industry 4.0 (I4.0) represents a significant step in the processes transformation in practically every industry, where the smart concept emerges in autonomous decisions and cyber-physical systems based production systems [1]. The role played by the usually referred technological pillars of I4.0 (such as internet of things (IoT), horizontal and vertical system integration, simulation, autonomous robots, big data and analytics, augmented reality, additive manufacturing, cloud computing and cybersecurity), based on technological advancements (mainly Information and Communications Technology (ICT)), in adhering to I4.0, are well known by the industry and academia (attending the huge number of research papers available), and have being implemented with more or less success. Notwithstanding the significant expected opportunities and impact of the fourth industrial revolution identified by researchers, experts are not convinced that the changes will be as significant as forecasted [2 - 4]. According to [5], only rare and recent attempts to understand the critical success factors of I4.0 implementation in manufacturing companies can be found in literature. A few recent studies reviewed in [5], point out that some of the critical factors are related to the management for I4.0. Cumulatively, the research in the field of management for I4.0, is still scarce, compared with the research on technologies for I4.0. The title of this Special Issue “Manufacturing System and Enterprise Management for Industry 4.0” is aligned with that concern and its content should be seen as a contribution to overcome management deficit problem of I4.0 implementation success. Nowadays, the challenges are related to the way how I4.0 is implemented and managed, in order to achieve the desired outcomes, economic, environmental, and social.First, our acknowledgments and greatest thanks go to Professor Bosko Rasuo, Editor-in-Chief of the FME Transactions, for his highest support and professionalism and, more importantly, his highest collaboration, understanding and patience during the development of this Special Issue. Next, our acknowledgments go to the authors, for their contributions and collaboration, and to the reviewers, for their great effort during the review process and for the suggestions they provided to the authors. Acknowledgments go also to our institutions, University of Minho and Polytechnic of Porto, and to the Research centres within which this project on this Special Issue has been developed, namely to ALGORITMI Research Center of the University of Minho and INESC TEC - Institute for Systems and Computer Engineering, Technology and Science. The guest editors want to acknowledge as well that this work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.info:eu-repo/semantics/publishedVersio

Guest editorial of the special issue 'human-centric, decentralised, and hyper automated cyber-physical systems'

The emergence of affordable communication and computer technologies has brought virtual and physical space closer together in recent years. Cyber-physical systems, which are the outcome of this confluence, have changed the condition of healthcare, medicine, the environment, sustainability, transportation, and energy. Cyber-Physical Systems (CPS) are a synthesis of virtual and physical technologies

Cognitive robotics and control

Postprint (published version

Mobile Intelligent Autonomous Systems

Mobile intelligent autonomous systems (MIAS) is a fast emerging research area. Although it can be regarded as a general R&D area, it is mainly directed towards robotics. Several important subtopics within MIAS research are:(i) perception and reasoning, (ii) mobility and navigation,(iii) haptics and teleoperation, (iv) image fusion/computervision, (v) modelling of manipulators, (vi) hardware/software architectures for planning and behaviour learning leadingto robotic architecture, (vii) vehicle-robot path and motionplanning/control, (viii) human-machine interfaces for interaction between humans and robots, and (ix) application of artificial neural networks (ANNs), fuzzy logic/systems (FLS),probabilistic/approximate reasoning (PAR), Bayesian networks(BN) and genetic algorithms (GA) to the above-mentioned problems. Also, multi-sensor data fusion (MSDF) playsvery crucial role at many levels of the data fusion process:(i) kinematic fusion (position/bearing tracking), (ii) imagefusion (for scene recognition), (iii) information fusion (forbuilding world models), and (iv) decision fusion (for tracking,control actions). The MIAS as a technology is useful for automation of complex tasks, surveillance in a hazardousand hostile environment, human-assistance in very difficultmanual works, medical robotics, hospital systems, autodiagnosticsystems, and many other related civil and military systems. Also, other important research areas for MIAScomprise sensor/actuator modelling, failure management/reconfiguration, scene understanding, knowledge representation, learning and decision-making. Examples ofdynamic systems considered within the MIAS would be:autonomous systems (unmanned ground vehicles, unmannedaerial vehicles, micro/mini air vehicles, and autonomousunder water vehicles), mobile/fixed robotic systems, dexterousmanipulator robots, mining robots, surveillance systems,and networked/multi-robot systems, to name a few.Defence Science Journal, 2010, 60(1), pp.3-4, DOI:http://dx.doi.org/10.14429/dsj.60.9

On the Role of Affective Properties in Hedonic and Discriminant Haptic Systems

Common haptic devices are designed to effectively provide kinaesthetic and/or cutaneous discriminative inputs to the users by modulating some physical parameters. However, in addition to this behavior, haptic stimuli were proven to convey also affective inputs to the brain. Nevertheless, such affective properties of touch are often disregarded in the design (and consequent validation) of haptic displays. In this paper we present some preliminary experimental evidences about how emotional feelings, intrinsically present while interacting with tactile displays, can be assessed. We propose a methodology based on a bidimensional model of elicited emotions evaluated by means of simple psychometric tests and statistical inference. Specifically, affective dimensions are expressed in terms of arousal and valence, which are quantified through two simple one-question psychometric tests, whereas statistical inference is based on rank-based non-parametric tests. In this work we consider two types of haptic systems: (i) a softness display, FYD-2, which was designed to convey purely discriminative softness haptic stimuli and (ii) a system designed to convey affective caress-like stimuli (by regulating the velocity and the strength of the “caress”) on the user forearm. Gender differences were also considered. In both devices, the affective component clearly depends on the stimuli and it is gender-related. Finally, we discuss how such outcomes might be profitably used to guide the design and the usage of haptic devices, in order to take into account also the emotional component, thus improving system performance