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

Multiple UAV systems: a survey

Nowadays, Unmanned Aerial Vehicles (UAVs) are used in many different applications. Using systems of multiple UAVs is the next obvious step in the process of applying this technology for variety of tasks. There are few research works that cover the applications of these systems and they are all highly specialized. The goal of this survey is to fill this gap by providing a generic review on different applications of multiple UAV systems that have been developed in recent years. We also present a nomenclature and architecture taxonomy for these systems. In the end, a discussion on current trends and challenges is provided.This work was funded by the Ministry of Economy, Industryand Competitiveness of Spain under Grant Nos. TRA2016-77012-R and BES-2017-079798Peer ReviewedPostprint (published version

Pedestrian Trajectory Prediction in Pedestrian-Vehicle Mixed Environments: A Systematic Review

Planning an autonomous vehicle's (AV) path in a space shared with pedestrians requires reasoning about pedestrians' future trajectories. A practical pedestrian trajectory prediction algorithm for the use of AVs needs to consider the effect of the vehicle's interactions with the pedestrians on pedestrians' future motion behaviours. In this regard, this paper systematically reviews different methods proposed in the literature for modelling pedestrian trajectory prediction in presence of vehicles that can be applied for unstructured environments. This paper also investigates specific considerations for pedestrian-vehicle interaction (compared with pedestrian-pedestrian interaction) and reviews how different variables such as prediction uncertainties and behavioural differences are accounted for in the previously proposed prediction models. PRISMA guidelines were followed. Articles that did not consider vehicle and pedestrian interactions or actual trajectories, and articles that only focused on road crossing were excluded. A total of 1260 unique peer-reviewed articles from ACM Digital Library, IEEE Xplore, and Scopus databases were identified in the search. 64 articles were included in the final review as they met the inclusion and exclusion criteria. An overview of datasets containing trajectory data of both pedestrians and vehicles used by the reviewed papers has been provided. Research gaps and directions for future work, such as having more effective definition of interacting agents in deep learning methods and the need for gathering more datasets of mixed traffic in unstructured environments are discussed.Comment: Published in IEEE Transactions on Intelligent Transportation System

Distributed Data Management in Vehicular Networks Using Mobile Agents

En los últimos años, las tecnologías de la información y las comunicaciones se han incorporado al mundo de la automoción gracias a sus avances, y han permitido la creación de dispositivos cada vez más pequeños y potentes. De esta forma, los vehículos pueden ahora incorporar por un precio asequible equipos informáticos y de comunicaciones.En este escenario, los vehículos que circulan por una determinada zona (como una ciudad o una autopista) pueden comunicarse entre ellos usando dispositivos inalámbricos que les permiten intercambiar información con otros vehículos cercanos, formando así una red vehicular ad hoc, o VANET (Vehicular Ad hoc Network). En este tipo de redes, las comunicaciones se establecen con conexiones punto a punto por medio de dispositivos tipo Wi-Fi, que permiten la comunicación con otros del mismo tipo dentro de su alcance, sin que sea necesaria la existencia previa de una infraestructura de comunicaciones como ocurre con las tecnologías de telefonía móvil (como 3G/4G), que además requieren de una suscripción y el pago de una tarifa para poder usarlas.Cada vehículo puede enviar información y recibirla de diversos orígenes, como el propio vehículo (por medio de los sensores que lleva incorporados), otros vehículos que se encuentran cerca, así como de la infraestructura de tráfico presente en las carreteras (como semáforos, señales, paneles electrónicos de información, cámaras de vigilancia, etc.). Todos estas fuentes pueden transmitir datos de diversa índole, como información de interés para los conductores (por ejemplo, atascos de tráfico o accidentes en la vía), o de cualquier otro tipo, mientras sea posible digitalizarla y enviarla a través de una red.Todos esos datos pueden ser almacenados localmente en los ordenadores que llevan los vehículos a medida que son recibidos, y sería muy interesante poder sacarles partido por medio de alguna aplicación que los explotara. Por ejemplo, podrían utilizarse los vehículos como plataformas móviles de sensores que obtengan datos de los lugares por los que viajan. Otro ejemplo de aplicación sería la de ayudar a encontrar plazas de aparcamiento libres en una zona de una ciudad, usando la información que suministrarían los vehículos que dejan una plaza libre.Con este fin, en esta tesis se ha desarrollado una propuesta de la gestión de datos basada en el uso de agentes móviles para poder hacer uso de la información presente en una VANET de forma eficiente y flexible. Esta no es una tarea trivial, ya que los datos se encuentran dispersos entre los vehículos que forman la red, y dichos vehículos están constantemente moviéndose y cambiando de posición. Esto hace que las conexiones de red establecidas entre ellos sean inestables y de corta duración, ya que están constantemente creándose y destruyéndose a medida que los vehículos entran y salen del alcance de sus comunicaciones debido a sus movimientos.En un escenario tan complicado, la aproximación que proponemos permite que los datos sean localizados, y que se puedan hacer consultas sobre ellos y transmitirlos de un sitio cualquiera de la VANET a otro, usando estrategias multi-salto que se adaptan a las siempre cambiantes posiciones de los vehículos. Esto es posible gracias a la utilización de agentes móviles para el procesamiento de datos, ya que cuentan con una serie de propiedades (como su movilidad, autonomía, adaptabilidad, o inteligencia), que hace que sean una elección muy apropiada para este tipo de entorno móvil y con un elevado grado de incertidumbre.La solución propuesta ha sido extensamente evaluada y probada por medio de simulaciones, que demuestran su buen rendimiento y fiabilidad en redes vehiculares con diferentes condiciones y en diversos escenarios.<br /

Guided Self-Organizing Particle Systems for Basic Problem Solving

In recent years researchers have shown increasing interest in swarm intelligence as a promising approach to adaptive distributed problem solving. Swarm intelligence consists of techniques inspired by nature, especially social insects and aggregations of animals, and even human interactions. They are based on self-organization (a system's overall behavior emerges from the local interactions among its relatively simple components) and are often decentralized and massively distributed. Particle systems are an approach to swarm intelligence that focus on collective movements, and have been used successfully for applications such as computer animation in graphics and control of movements of autonomous robotic vehicle teams. However, particle system techniques have not been applied substantially to problem solving beyond merely collective navigational tasks. In this dissertation, I present an extension to particle systems that incorporates top-down, high-level control to self-organizing mobile agents, thereby guiding the self-organizing process and making it possible for particle systems to undertake problem solving directed by goal-oriented behavior while retaining their decentralized, local nature. This extended particle system approach is critically evaluated through three experimental studies that are adapted from well-known problems in multi-agent systems: search and collect, cooperative transport and logistics. The results provide evidence that extended particle systems are capable of exhibiting behavior important for distributed problem solving, such as cooperative sensing, division of labor, sharing of information, and developing global strategies through local interactions. They also show that aggregated movements can be utilized to create coordination at different levels and phases of the performance of a task, whether those include navigation or not, making extended particle systems a useful tool in the construction of adaptive distributed systems

Facilitating Disaster Knowledge Management with Agent-Based Modelling

In developed countries, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. Nevertheless, accessing the appropriate plan in a timely manner and sharing activities between plans often requires domain knowledge and intimate knowledge of the plans in the first place. In this paper, we introduce an Agent-Based (AB) knowledge analysis framework to convert DISPLANs into a collection of knowledge units that can be stored in a unified repository. The repository of DM actions then enables the mixing and matching knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF) to allow the free flow access to the knowledge across the layers. We use the flood DISPLAN of the SES (State Emergency Service), an authoritative DM agency in NSW (New State Wales) State of Australia to illustrate and validate the developed framework

A Methodological Framework for Parametric Combat Analysis

This work presents a taxonomic structure for understanding the tension between certain factors of stability for game-theoretic outcomes such as Nash optimality, Pareto optimality, and balance optimality and then applies such game-theoretic concepts to the advancement of strategic thought on spacepower. This work successfully adapts and applies combat modeling theory to the evaluation of cislunar space conflict. This work provides evidence that the reliability characteristics of small spacecraft share similarities to the reliability characteristics of large spacecraft. Using these novel foundational concepts, this dissertation develops and presents a parametric methodological framework capable of analyzing the efficacy of heterogeneous force compositions in the context of space warfare. This framework is shown to be capable of predicting a stochastic distribution of numerical outcomes associated with various modes of conflict and parameter values. Furthermore, this work demonstrates a general alignment in results between the game-theoretic concepts of the framework and Media Interaction Warfare Theory in terms of evaluating force efficacy, providing strong evidence for the validity of the methodological framework presented in this dissertation