An Overview of Self-Adaptive Technologies Within Virtual Reality Training

This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training

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

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Immersive analytics for oncology patient cohorts

This thesis proposes a novel interactive immersive analytics tool and methods to interrogate the cancer patient cohort in an immersive virtual environment, namely Virtual Reality to Observe Oncology data Models (VROOM). The overall objective is to develop an immersive analytics platform, which includes a data analytics pipeline from raw gene expression data to immersive visualisation on virtual and augmented reality platforms utilising a game engine. Unity3D has been used to implement the visualisation. Work in this thesis could provide oncologists and clinicians with an interactive visualisation and visual analytics platform that helps them to drive their analysis in treatment efficacy and achieve the goal of evidence-based personalised medicine. The thesis integrates the latest discovery and development in cancer patients’ prognoses, immersive technologies, machine learning, decision support system and interactive visualisation to form an immersive analytics platform of complex genomic data. For this thesis, the experimental paradigm that will be followed is in understanding transcriptomics in cancer samples. This thesis specifically investigates gene expression data to determine the biological similarity revealed by the patient's tumour samples' transcriptomic profiles revealing the active genes in different patients. In summary, the thesis contributes to i) a novel immersive analytics platform for patient cohort data interrogation in similarity space where the similarity space is based on the patient's biological and genomic similarity; ii) an effective immersive environment optimisation design based on the usability study of exocentric and egocentric visualisation, audio and sound design optimisation; iii) an integration of trusted and familiar 2D biomedical visual analytics methods into the immersive environment; iv) novel use of the game theory as the decision-making system engine to help the analytics process, and application of the optimal transport theory in missing data imputation to ensure the preservation of data distribution; and v) case studies to showcase the real-world application of the visualisation and its effectiveness

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

Advancing automation and robotics technology for the Space Station and for the US economy, volume 2

In response to Public Law 98-371, dated July 18, 1984, the NASA Advanced Technology Advisory Committee has studied automation and robotics for use in the Space Station. The Technical Report, Volume 2, provides background information on automation and robotics technologies and their potential and documents: the relevant aspects of Space Station design; representative examples of automation and robotics; applications; the state of the technology and advances needed; and considerations for technology transfer to U.S. industry and for space commercialization

Commande collaborative pour un fauteuil roulant intelligent

RÉSUMÉ Le contrôle partagé est l’une des plus importantes problématiques à laquelle les chercheurs font face dans le domaine de l’interaction entre l’Homme et la machine. Il est souvent appliqué pour les véhicules motorisés avec contrôle assisté tels que les fauteuils roulants électriques, les marcheurs médicaux, les véhicules d’exploration spatiale et l’exploration sous-marine... Il est aussi utilisé pour la robotique manipulatrice avec les modules de téléopération des bras manipulateurs et des instruments chirurgicaux. Le but de ce mémoire est le développement d’un système de contrôle collaboratif entre un opérateur humain et un Fauteuil Roulant Motorisé Intelligent (FRMI) afin de faciliter les tâches de navigation pour les personnes à mobilité réduite dont la maladie affecte leur aptitude pour contrôler la machine d’une manière précise. Nous proposons donc un module de navigation qui se base théoriquement sur les processus de décision de Markov afin d’estimer d’une part l’intention du pilote et corriger d’autre part ses commandes dans le cas de danger. Ce module donne une importance majeure aux signaux de contrôle de l’humain qui est considéré dans tout le travail comme étant la source primaire de décision. Par conséquent, le module se contente uniquement de l’assister. Deux modes de fonctionnement de notre contrôleur collaboratif ont été créés afin de satisfaire divers styles de conduite et fournir des degrés d’assistances différents. Pour le premier mode, l’utilisateur fixe une ou plusieurs destinations sur la carte de l’environnement créée par le fauteuil en temps réel et ainsi pendant qu’il navigue librement, la machine estime son intention en observant ses commandes pour l’aider à atteindre la destination la plus probable en évitant tous les dangers. Par contre, pour le deuxième mode de fonctionnement, nous présentons un degré d’assistance plus élevé, autrement dit les rôles sont inversés et c’est le FRMI qui se chargera de toutes les tâches de navigation (planification de trajectoire, détermination de commandes de vitesse, évitement d’obstacle...). Le rôle du pilote se résume initialement dans l’expression d’une destination finale mais il peut reprendre le contrôle à tout instant si par exemple il change d’avis pendant la navigation et il veut atteindre un point intermédiaire sur la carte. Notre travail contribue à l’amélioration de l’interaction entre l’humain et la machine en partageant le contrôle pendant la navigation. Il assure aussi une sécurité supplémentaire en prévoyant les risques d’accrochage pour réduire la vitesse en cas de danger non détecté par l’usager.----------ABSTRACT Shared autonomy or shared control is one of the most important challenge that pushes researchers to focus more and more on the application of this kind of concept in the assistive technology. It adequately accommodates the living standards of the elderly and disabled communities. It helps them to accomplish the daily tasks with comfort and no assistance. To this end, we have chosen the Partially Observable Markov Decision Process in order to formulate our shared control of the semi-autonomous module added to our SmartWheeler in order to facilitate navigation tasks and to control the machine in a precise manner. Our decision process estimates firstly the intention of the driver and then corrects all his commands in case of danger. This gives the operator a lot of freedom in controlling the machine. As we consider human mind as a very good item to resolve quickly complex problem, it represents the primary source of decision in our work. Moreover, two modes of operation in our collaborative controller have been created to suit the driving style and provide different degrees of assistance. The user has to set one or more goals in the map. Then, with the first mode, he/she can navigate freely between all those goals. The SmartWheeler estimates his/her intention in order to help him/her to reach the intended destination. For the second mode of operation, we set a higher degree of assistance. The two controlling agents (human and machine) swap roles, so that the collaborative module takes in charge all navigation tasks (path planning, speed controls, obstacle avoidance...) and the pilot after choosing the final destination has to let the machine do the job. However, he/she also can take control at any time he/she wants. For example, if he/she changes his/her mind during the navigation and wants to reach an other goal, he/she has to give some velocity commands with the joystick and the module switches automatically to the first mode. Our work contributes to the improvement of human-machine interaction. It provides additional security by detecting collisions and dangerous scenarios. It reduces the speed and corrects orientations. We performed a user study to test our shared autonomy in several scenarios. The results show that our system did not cause any conflict between the two controlling agents. The subjects were not able to perceive the intervention of the module and they felt safer using our algorithm

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics