by Theodore Patkos (ICS-FORTH) and Zsolt Viharos (SZTAKI)
The wave of popularity of modern Artificial Intelligence (AI) systems is creating well-justified expectations that its application to diverse domains will lead to even bigger advancements in the future. At the same time, there is an open debate in the research community regarding the limitations of existing methods, and whether the current success can scale up to a broader spectrum of problems than those current AI is focusing on. Especially considering that modern intelligent systems are affecting our everyday lives at an increasing pace, the request for future intelligent machines is to exhibit capabilities that are not only effective, but also closer to human intuition and intellect.
by Konstantinos Papoutsakis (FORTH-ICS), Maria Pateraki (National Technical University of Athens & FORTH-ICS)
Visual monitoring of human behaviour during work activities is a key ingredient for task progress monitoring and fluency in human-robot collaboration as well as for supporting worker safety in industrial environments. The proposed framework employs low-cost, fixed sensors in a realistic manufacturing environment for the real-time observation of work postures and actions during car door assembly actions, as part of the FELICE project. This task aims to estimate workers’ states and potential ergonomic risks in order to initiate robot collaboration with a specific worker, delegate tasks to the robot and ease the physical burden, while also contributing to the well-being of the worker.
by Christos Anagnostopoulos (ISI, ATHENA R.C), Gerasimos Arvanitis (University of Patras), Nikos Piperigkos (ISI, ATHENA R.C), Aris S. Lalos (ISI, ATHENA R.C) and Konstantinos Moustakas (University of Patras)
Robot behaviour affects worker safety, health and comfort. Enhancing operator physical monitoring reduces the risk of accidents and musculoskeletal disorders. Within CPSoSAware, we propose a multi-stereo camera system and novel distributed fusion approaches that are executed on accelerated AI platforms, continuously monitoring the posture of the operators and assisting them to avoid uncomfortable and unsafe postures, based on their anthropometric characteristics and a real-time risk assessment standard methodology.
by Mario Vento, Antonio Greco and Vincenzo Carletti (University of Salerno)
UNISA is working on a more natural human-robot interaction and cooperation in manual assembly lines through speech and gesture commands. Where are we with the FELICE project?
by Antonello Calabrò and Eda Marchetti (ISTI-CNR)
Making cobot safety protocols closer to a cookbook than to methodologies: Let users implement protocols without overhead in knowledge and understanding of the procedures.
by Mohamed Behery, Philipp Brauner, Martina Ziefle and Gerhard Lakemeyer (RWTH Aachen University)
Shorter product lifecycles, more product variants, individualised production, and the desire for sustainable production call for agile control frameworks that enable smarter robotic control and collaborating human-robot teams. We propose generalising and standardising “Behaviour Trees” that use human action nodes as a process model and task-execution-monitoring approach for human-robot collaborative assembly processes to increase the agility of human-robot teams while ensuring a safe and trusted human-robot interaction. Within the DFG (Deutsche Forschungsgemeinschaft) funded Cluster of Excellence “Internet of Production”, we take a cross-disciplinary approach to conceptualisation and validation to ensure algorithmic soundness, technical viability, and social acceptance by the workers of increasingly agile human-robot teams.
by Antero Karvonen (VTT) and Pertti Saariluoma (Jyväskylä University)
AI is replacing and supporting people in many intelligence-requiring tasks. Therefore, it is essential to consider the conceptual grounds of designing future technical artefacts and technologies for practical use. We are developing two new practical design tools: cognitive mimetics and human digital twins for AI designers. Cognitive mimetics analyses human information processing to be mimicked by intelligent technologies. Human digital twins provide a tool for modelling what people do based on the results of cognitive mimetics. Together they provide a new way of designing intelligent technology in individual tasks and industrial contexts.
by Maria Dagioglou (NCSR ‘Demokritos’, Greece) and Vangelis Karkaletsis (NCSR ‘Demokritos’, Greece)
For this teaser we were asked to describe what is the article about, who is doing what and why. Fittingly enough, this is literally what we discuss in this article: in human-robot collaboration, who is doing what and why?
by Loizos Michael (Open University of Cyprus & CYENS Center of Excellence)
AI systems that are compatible with human cognition will not come as an afterthought by patching up opaque models with post-hoc explainability. This article reports on our research program to develop Machine Coaching, a computationally efficient and cognitively light paradigm that supports a form of interactive and developmental machine learning, through supervision that is not only functional, on “what” decisions should be made, but also structural, on “how” they should be made. We discuss the role that this paradigm can play in neural-symbolic systems, in operationalizing fast intuitive and slow deliberative thinking, and in supporting the explainability and contestability of AI systems by design.
by Antonis Kakas (University of Cyprus)
How can machines think in a human-like way? How can they argue about and debate issues? Could machines argue on our behalf? Cognitive Machine Argumentation studies these questions based on a synthesis of Computational Argumentation in AI with studies on human reasoning in cognitive psychology, philosophy and other disciplines.
by Christian Thomay and Benedikt Gollan (Research Studios Austria FG), Anna-Sophie Ofner (Universität Mozarteum Salzburg) and Thomas Scherndl (Paris Lodron Universität Salzburg)
We propose using Cognitive AI methods for use in multimodal arts installations to create interactive systems that learn from their visitors. Researchers and artists from Research Studios Austria FG and the Universität Mozarteum Salzburg have created a multimodal installation in which users can use hand gestures to interact with individual instruments playing a Mozart string quartet. In this article, we outline this installation and our plans to realise Cognitive AI methods that learn from their users, thereby improving the performance of gesture recognition as well as usability and user experience.
by Tamás Cserteg, Anh Tuan Hoang, Krisztián Kis, János Csempesz (SZTAKI) and Zsolt János Viharos, (SZTAKI and John von Neumann University)
The combination of cognitive AI and robotics has already had a significant impact on the way we live. Novel developed solutions not only cover industrial applications, but are widely spread in the field of social robotics as well. To bring cognitive AI and robotics closer to people not exposed to these technologies on a day-to-day basis, a portrait-drawing demonstrator, called Piktor-O-Bot has been developed at SZTAKI. Over the past year and a half, portraits of more than a thousand people have been drawn, which shows great interest in the demonstrator and that people are genuinely interested in cognitive robotic applications.
by Hayley Hung (Delft University of Technology)
Researchers at the Socially Perceptive Computing Lab at Delft University of Technology in the Netherlands investigate novel ways to measure our quality of experience in social encounters. Their aim is to understand the difference between good and bad social encounters, from speed-dates, to professional networking events, to long-term simulated space missions. This paves the way for the development of technologies to understand and ultimately improve our social encounters.
by Benedetta Catricalà, Marco Manca, Fabio Paternò, Carmen Santoro and Eleonora Zedda (ISTI-CNR)
We present an approach to novel digital cognitive training through serious games able to adapt to personally relevant material from the older adult’s life. The games are based on memories associated with the older adult’s biography, thus making interactions personalised, relevant, and more engaging. The serious games are accessed through humanoid robots, which can make the training exercise more engaging because of their human-like behaviour.
by Anh Tuan Hoang (SZTAKI) and Zsolt János Viharos (SZTAKI and John von Neumann University)
Human Activity Recognition (HAR) is a prevalent topic in the field of cognitive intelligence, closely related to Human-Centred Artificial Intelligence (HCAI). The emergence of deep learning has brought breakthroughs in many HAR problems. This research proposes a novel search algorithm to determine the optimal deep neural model structure that considers the internal relationships as well as the information content incorporated in the data, and as a result serving with superior capabilities in recognition of various human activity types.