1,704 research outputs found

    Multi Agent Systems

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    Research on multi-agent systems is enlarging our future technical capabilities as humans and as an intelligent society. During recent years many effective applications have been implemented and are part of our daily life. These applications have agent-based models and methods as an important ingredient. Markets, finance world, robotics, medical technology, social negotiation, video games, big-data science, etc. are some of the branches where the knowledge gained through multi-agent simulations is necessary and where new software engineering tools are continuously created and tested in order to reach an effective technology transfer to impact our lives. This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. We hope that this book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems

    Virtual mechanical product disassembly sequences based on disassembly order graphs and time measurement units

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    Recently, the approach that defines the total life cycle assessment (LCA) and the end of life (EoL) in the early design phases is becoming even more promising. Literature evidences many advantages in terms of the saving of costs and time and in the fluent organization of the whole design process. Design for disassembly (DfD) offers the possibility of reducing the time and cost of disassembling a product and accounts for the reusing of parts and of the dismantling of parts, joints, and materials. The sequence of disassembly is the ordered way to extract parts from an assembly and is a focal item in DfD because it can deeply influence times and operations. In this paper, some disassembly sequences are evaluated, and among them, two methods for defining an optimal sequence are provided and tested on a case study of a mechanical assembly. A further sequence of disassembly is provided by the authors based on experience and personal knowledge. All three are analyzed by the disassembly order graph (DOG) approach and compared. The operations evaluated have been converted in time using time measurement units (TMUs). As result, the best sequence has been highlighted in order to define a structured and efficient disassembly

    Workshop sensing a changing world : proceedings workshop November 19-21, 2008

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    Diagnosing Robotic Swarms (Dr. Swarm)

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    Troubleshooting a robotic swarm can be a daunting task due to large quantities of information to sift through and many potential sources of problems. Currently there are no widely adopted swarm diagnostic systems. We developed Dr. Swarm, a mobile application which combines state-of-the-art AR technology and existing visualization techniques to create a new kind of diagnostic tool for swarm robotics. Dr. Swarm enables developers to expose the behavior of swarm systems through intuitive visualizations and assists with troubleshooting swarm applications

    Design Issues and in Field Tests of the New Sustainable Tractor LOCOSTRA

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    first, in Italy, focusing on the agricultural application of the machine, in natural scenarios with different ground and vegetatio

    Virtual Reality Games for Motor Rehabilitation

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    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

    A Low-Cost Experimental Testbed for Multi-Agent System Coordination Control

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    A multi-agent system can be defined as a coordinated network of mobile, physical agents that execute complex tasks beyond their individual capabilities. Observations of biological multi-agent systems in nature reveal that these ``super-organisms” accomplish large scale tasks by leveraging the inherent advantages of a coordinated group. With this in mind, such systems have the potential to positively impact a wide variety of engineering applications (e.g. surveillance, self-driving cars, and mobile sensor networks). The current state of research in the area of multi-agent systems is quickly evolving from the theoretical development of coordination control algorithms and their computer simulations to experimental validations on proof-of-concept testbeds using small-scale mobile robotic platforms. An in-house testbed would allow for rapid prototyping and validation of control algorithms, and potentially lead to new research directions spawned by experimentally-observed issues. To this end, a custom experimental testbed, TIGER Square, has been designed, developed, built, and tested at Louisiana State University. In this work, the completed design and test results for a centralized testbed is presented. That is, the individual robots follow an overarching control entity and are reliant on a global structure, such as a central processing computer. As part of the validation process, a series of formation control experiments were executed to assess the performance of the testbed. In order to eliminate single-point failures, a multi-agent system must be fully decentralized or distributed. This means that the responsibilities of processing, localization, and communication are distributed to each agent. Therefore, this work concludes with the introduction of a prototype localization module that will be integrated into the existing centralized testbed. This initial step allows for the future decentralization of TIGER Square and opens the path to achieve a fully capable multi-agent system testbed

    Toward a Bio-Inspired System Architecting Framework: Simulation of the Integration of Autonomous Bus Fleets & Alternative Fuel Infrastructures in Closed Sociotechnical Environments

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    Cities are set to become highly interconnected and coordinated environments composed of emerging technologies meant to alleviate or resolve some of the daunting issues of the 21st century such as rapid urbanization, resource scarcity, and excessive population demand in urban centers. These cybernetically-enabled built environments are expected to solve these complex problems through the use of technologies that incorporate sensors and other data collection means to fuse and understand large sums of data/information generated from other technologies and its human population. Many of these technologies will be pivotal assets in supporting and managing capabilities in various city sectors ranging from energy to healthcare. However, among these sectors, a significant amount of attention within the recent decade has been in the transportation sector due to the flood of new technological growth and cultivation, which is currently seeing extensive research, development, and even implementation of emerging technologies such as autonomous vehicles (AVs), the Internet of Things (IoT), alternative xxxvi fueling sources, clean propulsion technologies, cloud/edge computing, and many other technologies. Within the current body of knowledge, it is fairly well known how many of these emerging technologies will perform in isolation as stand-alone entities, but little is known about their performance when integrated into a transportation system with other emerging technologies and humans within the system organization. This merging of new age technologies and humans can make analyzing next generation transportation systems extremely complex to understand. Additionally, with new and alternative forms of technologies expected to come in the near-future, one can say that the quantity of technologies, especially in the smart city context, will consist of a continuously expanding array of technologies whose capabilities will increase with technological advancements, which can change the performance of a given system architecture. Therefore, the objective of this research is to understand the system architecture implications of integrating different alternative fueling infrastructures with autonomous bus (AB) fleets in the transportation system within a closed sociotechnical environment. By being able to understand the system architecture implications of alternative fueling infrastructures and AB fleets, this could provide performance-based input into a more sophisticated approach or framework which is proposed as a future work of this research

    Hardware neural systems for applications: a pulsed analog approach

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