Cyber Physical Systems Oriented Robot Development Platform

AbstractThe development of systems, of various levels of complexity that can integrate physical with virtual components has become a priority for research in the context of emerging paradigms such as Cyber-Physical Systems or Internet for the Future. The authors propose a Robotic Development Platform architecture that integrates principles of Cyber-Physical Systems. The proposed architecture, is scalable, by facilitating the integration of different existing development and simulation tools and will allow robot systems to be tested in different environments, with different characteristics, and facilitate the integration of real world simulation with virtual environment simulation

A cyber-physical systems approach to cognitive enterprise

Internet of Things and Cyber-Physical Systems are paradigms that have an important influence on enterprise systems architecture and implementation. The Cognitive Manufacturing as well as the Cognitive Enterprise are emerging models, related to these paradigms, that intend to redesign in the Enterprise Information Model by integrating new information processing and problem-solving methods. This paper intends to analyses and discuss Cognitive Enterprise enablers and principles considering an approach based on models of human brain perception-reasoning-learning processes

Neuro-inspired Framework for Cognitive Manufacturing Control

There are currently certain categories of manufacturing enterprises whose structure, organization and operating context have an extremely high degree of complexity, especially due to the way in which their various components interact and influence each other. For them, a series of paradigms have been developed, including intelligent manufacturing, smart manufacturing, cognitive manufacturing; which are based equally on information and knowledge management, management and interpretation of data flows and problem solving approaches. This work presents a new vision regarding the evolution of the future enterprise based on concepts and attributes acquired from the field of biology. Our approach addresses in a systemic manner the structural, functional, and behavioral aspects of the enterprise, seen as a complex dynamic system. In this article we are proposing an architecture and management methodology based on the human brain, where the problem solving is achieved by Perception – Memory – Learning and Behavior Generation mechanisms. In order to support the design of such an architecture and to allow a faster learning process, a software modeling and simulation platform was developed and is briefly presented

High Precision Positioning with Multi-Camera Setups: Adaptive Kalman Fusion Algorithm for Fiducial Markers

The paper addresses the problem of fusing the measurements from multiple cameras in order to estimate the position of fiducial markers. The objectives are to increase the precision and to extend the working area of the system. The proposed fusion method employs an adaptive Kalman algorithm which is used for calibrating the setup of cameras as well as for estimating the pose of the marker. Special measures are taken in order to mitigate the effect of the measurement noise. The proposed method is further tested in different scenarios using a Monte Carlo simulation, whose qualitative precision results are determined and compared. The solution is designed for specific positioning and alignment tasks in physics experiments, but also, has a degree of generality that makes it suitable for a wider range of applications

Towards A General Systems Theory Approach for Developing Concurrent Engineering Science

Information, as a specific commodity, sustains our knowledge production in every domain of human activities. But the Knowledge-based Economy (KbE), requires intensive information and Knowledge Management. The KM is the key-factor of enterprises competitiveness (LS- large scale enterprises; SME- small and medium size Enterprise ;μE- micro size enterprises). Even the e-workers, immersed in Professional Virtual Communities must use efectively both basic concepts, methodology, methods and techniques from concurent engineering science. To design the Complex Adaptive Systems, is our our long-term research target. The present paper is an ambitious attempt to initiate a global collaborative project for the DCCE scientifically foundation based on General Systems Theory holistic approach.Pages: 3-1

An Hybrid Approach for Urban Traffic Prediction and Control in Smart Cities

Smart cities are complex, socio-technological systems built as a strongly connected System of Systems, whose functioning is driven by human–machine interactions and whose ultimate goals are the well-being of their inhabitants. Consequently, controlling a smart city is an objective that may be achieved by using a specific framework that integrates algorithmic control, intelligent control, cognitive control and especially human reasoning and communication. Among the many functions of a smart city, intelligent transportation is one of the most important, with specific restrictions and a high level of dynamics. This paper focuses on the application of a neuro-inspired control framework for urban traffic as a component of a complex system. It is a proof of concept for a systemic integrative approach to the global problem of smart city management and integrates a previously designed urban traffic control architecture (for the city of Bucharest) with the actual purpose of ensuring its proactivity by means of traffic flow prediction. Analyses of requirements and methods for prediction are performed in order to determine the best way for fulfilling the perception function of the architecture with respect to the traffic control problem definition. A parametric method and an AI-based method are discussed in order to predict the traffic flow, both in the short and long term, based on real data. A brief comparative analysis of the prediction performances is also presented

A Perceptive Interface for Intelligent Cyber Enterprises

Large scale, complex, networked enterprises, as may be considered (trans)national energy systems, multi-national manufacturing enterprises, smart cities a.s.o. are structures that can be characterized as systems of systems (SoS) and, as such, require specific modelling paradigms and control architectures to ensure their successful running. Their main characteristic is the necessity of solving practically one-of-a-kind problems with respect to the external context and internal configuration, thus dealing with dynamically evolving flows of data and information. The paper introduces the concept of intelligent cyber-enterprise, as an integrating paradigm that uses information and knowledge dynamics, in order to model and control SoS, especially focusing on the importance of appropriately adapt external and internal perception of an enterprise through a new generation of sensorial systems—the perceptive interfaces. The authors analyze sensing and perception in relation to intelligent cyber enterprise model and propose an implementation for a perceptive system interface