Search results for "Control and Systems Engineering"
showing 10 items of 994 documents
An introduction to knowledge computing
2014
This paper deals with the challenges related to self-management and evolution of massive knowledge collections. We can assume that a self-managed knowledge graph needs a kind of a hybrid of: an explicit declarative self-knowledge (as knowledge about own properties and capabilities) and an explicit procedural self-knowledge (as knowledge on how to utilize own properties and the capabilities for the self-management).We offer an extension to a traditional RDF model of describing knowledge graphs according to the Semantic Web standards so that it will also allow to a knowledge entity to autonomously perform or query from remote services different computational executions needed. We also introdu…
Localization Based on Parallel Robots Kinematics as an Alternative to Trilateration
2022
In this article, a new scheme for range-based localization is proposed. The main goal is to estimate the position of a mobile point based on distance measurements from fixed devices, called anchors, and on inertial measurements. Due to the nonlinear nature of the problem, an analytic relation to compute the position starting from these measurements does not exist, and often trilateration methods are used, generally based on least-square algorithms. The proposed scheme is based on the modeling of the localization process as a parallel robot, thereby methodologies and control algorithms used in the robotic area can be exploited. In particular, a closed-loop control system is designed for trac…
MAC Protocols for Wake-up Radio: Principles, Modeling and Performance Analysis
2018
[EN] In wake-up radio (WuR) enabled wireless sensor networks (WSNs), a node triggers a data communication at any time instant by sending a wake-up call (WuC) in an on-demand manner. Such wake-up operations eliminate idle listening and overhearing burden for energy consumption in duty-cycled WSNs. Although WuR exhibits its superiority for light traffic, it is inefficient to handle high traffic load in a network. This paper makes an effort towards improving the performance of WuR under diverse load conditions with a twofold contribution. We first propose three protocols that support variable traffic loads by enabling respectively clear channel assessment (CCA), backoff plus CCA, and adaptive …
M-GRASP: A GRASP With Memory for Latency-Aware Partitioning Methods in DVE Systems
2009
A necessary condition for providing quality of service to distributed virtual environments (DVEs) is to provide a system response below a maximum threshold to the client computers. In this sense, latency-aware partitioning methods try to provide response times below the threshold to the maximum number of client computers as possible. These partitioning methods should find an assignment of clients to servers that optimizes system throughput, system latency, and partitioning efficiency. In this paper, we present a new algorithm based on greedy randomized adaptive search procedure with memory for finding the best solutions as possible to this problem. We take into account several different alt…
Energy market segmentation for distributed energy resources implementation purposes
2007
The new power market scene has made its actors aware of the importance of offering customers a set of products according to their specific needs. At the same time, a desirable massive deployment of distributed energy resources would require that the products be designed for specific purposes for each type of customer. For these reasons, it is essential to identify the energy behaviour of different customer segments existing in the electricity market. This paper presents a segmentation methodology that allows the identification of different types of customers in accordance with their energy use. This segmentation is conceptually different from the one that is currently performed by the utili…
Automatic place detection and localization in autonomous robotics
2007
This paper presents an approach for the simultaneous learning and recognition of places applied to autonomous robotics. While noteworthy results have been achieved with respect to off-line training process for appearance-based navigation, novel issues arise when recognition and learning are simultaneous and unsupervised processes. The approach adopted here uses a Gaussian mixture model estimated by a novel incremental MML-EM to model the probability distribution of features extracted by image-preprocessing. A place detector decides which features belong to which place integrating odometric information and a hidden Markov model. Tests demonstrate that the proposed system performs as well as …
On the advantages of combining differential algorithms and log-polar vision for detection of self-motion from a mobile robot
2001
Abstract This paper describes the design and implementation on programmable hardware (FPGAs) of an algorithm for the detection of self-mobile objects as seen from a mobile robot. In this context, ‘self-mobile’ refers to those objects that change in the image plane due to their own movement, and not to the movement of the camera on board of the mobile robot. The method consists on adapting the original algorithm from Chen and Nandhakumar [A simple scheme for motion boundary detection, in: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1994] by using foveal images obtained with a special camera whose optical axis points towards the direction of advance. It i…
Ontology-based state representations for intention recognition in human–robot collaborative environments
2013
In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level state relationships that must be true for future actions to occur, a robot can use the detailed state information described in this paper to infer the probability of subsequent actions occurring. This would allow the robot to better help the …
A Cognitive Framework for Imitation Learning
2006
Abstract In order to have a robotic system able to effectively learn by imitation, and not merely reproduce the movements of a human teacher, the system should have the capabilities of deeply understanding the perceived actions to be imitated. This paper deals with the development of cognitive architecture for learning by imitation in which a rich conceptual representation of the observed actions is built. The purpose of the following discussion is to show how this Conceptual Area can be employed to efficiently organize perceptual data, to learn movement primitives from human demonstration and to generate complex actions by combining and sequencing simpler ones. The proposed architecture ha…
Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)
2017
International audience; This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the pred…