Trusted Artificial Intelligence in Manufacturing; Trusted Artificial Intelligence in Manufacturing

The successful deployment of AI solutions in manufacturing environments hinges on their security, safety and reliability which becomes more challenging in settings where multiple AI systems (e.g., industrial robots, robotic cells, Deep Neural Networks (DNNs)) interact as atomic systems and with humans. To guarantee the safe and reliable operation of AI systems in the shopfloor, there is a need to address many challenges in the scope of complex, heterogeneous, dynamic and unpredictable environments. Specifically, data reliability, human machine interaction, security, transparency and explainability challenges need to be addressed at the same time. Recent advances in AI research (e.g., in deep neural networks security and explainable AI (XAI) systems), coupled with novel research outcomes in the formal specification and verification of AI systems provide a sound basis for safe and reliable AI deployments in production lines. Moreover, the legal and regulatory dimension of safe and reliable AI solutions in production lines must be considered as well. To address some of the above listed challenges, fifteen European Organizations collaborate in the scope of the STAR project, a research initiative funded by the European Commission in the scope of its H2020 program (Grant Agreement Number: 956573). STAR researches, develops, and validates novel technologies that enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, the project researches and delivers approaches that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. This book is co-authored by the STAR consortium members and provides a review of technologies, techniques and systems for trusted, ethical, and secure AI in manufacturing. The different chapters of the book cover systems and technologies for industrial data reliability, responsible and transparent artificial intelligence systems, human centered manufacturing systems such as human-centred digital twins, cyber-defence in AI systems, simulated reality systems, human robot collaboration systems, as well as automated mobile robots for manufacturing environments. A variety of cutting-edge AI technologies are employed by these systems including deep neural networks, reinforcement learning systems, and explainable artificial intelligence systems. Furthermore, relevant standards and applicable regulations are discussed. Beyond reviewing state of the art standards and technologies, the book illustrates how the STAR research goes beyond the state of the art, towards enabling and showcasing human-centred technologies in production lines. Emphasis is put on dynamic human in the loop scenarios, where ethical, transparent, and trusted AI systems co-exist with human workers. The book is made available as an open access publication, which could make it broadly and freely available to the AI and smart manufacturing communities

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Ubiquitous Integration and Temporal Synchronisation (UbilTS) framework : a solution for building complex multimodal data capture and interactive systems

Contemporary Data Capture and Interactive Systems (DCIS) systems are tied in with various technical complexities such as multimodal data types, diverse hardware and software components, time synchronisation issues and distributed deployment configurations. Building these systems is inherently difficult and requires addressing of these complexities before the intended and purposeful functionalities can be attained. The technical issues are often common and similar among diverse applications. This thesis presents the Ubiquitous Integration and Temporal Synchronisation (UbiITS) framework, a generic solution to address the technical complexities in building DCISs. The proposed solution is an abstract software framework that can be extended and customised to any application requirements. UbiITS includes all fundamental software components, techniques, system level layer abstractions and reference architecture as a collection to enable the systematic construction of complex DCISs. This work details four case studies to showcase the versatility and extensibility of UbiITS framework’s functionalities and demonstrate how it was employed to successfully solve a range of technical requirements. In each case UbiITS operated as the core element of each application. Additionally, these case studies are novel systems by themselves in each of their domains. Longstanding technical issues such as flexibly integrating and interoperating multimodal tools, precise time synchronisation, etc., were resolved in each application by employing UbiITS. The framework enabled establishing a functional system infrastructure in these cases, essentially opening up new lines of research in each discipline where these research approaches would not have been possible without the infrastructure provided by the framework. The thesis further presents a sample implementation of the framework on a device firmware exhibiting its capability to be directly implemented on a hardware platform. Summary metrics are also produced to establish the complexity, reusability, extendibility, implementation and maintainability characteristics of the framework.Engineering and Physical Sciences Research Council (EPSRC) grants - EP/F02553X/1, 114433 and 11394