Search results for "Topological map"

showing 4 items of 4 documents

Attention-Based Landmark Selection in Autonomous Robotics

2007

This paper describes a robotic architecture that uses visual attention mechanisms for autonomous navigation in unknown indoor environments. A foveation mechanism based on a bottom-up attention system allows the robot to autonomously select landmarks, defined as salient points in the camera images. Landmarks are memorized in a behavioral fashion by coupling sensing and acting to achieve a representation that is view and scale independent. Selected landmarks are stored in a topological map. During the navigation a top-down mechanism controls the attention system to achieve robot localization. Experiments and results show that our system is robust to noise and odometric errors, being at the sa…

Social robotLandmarkbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONRoboticsMobile robotMobile robot navigationGeographyRobotComputer visionTopological mapNoise (video)Artificial intelligencebusiness
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Attention-based environment perception in autonomous robotics

2007

This paper describes a robotic architecture that uses visual attention mechanisms for autonomous navigation in unknown indoor environments. A foveation mechanism based on classical bottom-up gaze shifts allows the robot to autonomously select landmarks, defined as salient points in the camera images. Landmarks are memorized in a behavioral fashion, coupling sensing and acting to achieve a representation view and scale independent. Selected landmarks are stored in a topological map; during the navigation a top-down mechanism controls the attention system to achieve robot localization. Experiments and results show that our system is robust to noise and odometric errors, being at the same time…

Social robotbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMobile robotRoboticsrobotGazeMobile robot navigationRobotComputer visionAttentionArtificial intelligenceNoise (video)Topological mapbusiness
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Neural Classification of Compost Maturity by Means of the Self-Organising Feature Map Artificial Neural Network and Learning Vector Quantization Algo…

2019

Self-Organising Feature Map (SOFM) neural models and the Learning Vector Quantization (LVQ) algorithm were used to produce a classifier identifying the quality classes of compost, according to the degree of its maturation within a period of time recorded in digital images. Digital images of compost at different stages of maturation were taken in a laboratory. They were used to generate an SOFM neural topological map with centres of concentration of the classified cases. The radial neurons on the map were adequately labelled to represent five suggested quality classes describing the degree of maturation of the composted organic matter. This enabled the creation of a neural separator classify…

non-parametric classificationComputer science020209 energyHealth Toxicology and Mutagenesislcsh:Medicine02 engineering and technology010501 environmental sciencesengineering.material01 natural sciencesArticleDigital imageSoftwareArtificial Intelligence0202 electrical engineering electronic engineering information engineeringLearningTopological map0105 earth and related environmental sciencesLVQ algorithmLearning vector quantizationArtificial neural networkSOFM neural networkCompostbusiness.industryCompostinglcsh:RPublic Health Environmental and Occupational Health<i>LVQ</i> algorithmengineeringNeural Networks ComputerbusinessClassifier (UML)AlgorithmAlgorithmsSoftwareInternational Journal of Environmental Research and Public Health
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A Communication-Aware Topological Mapping Technique for NoCs

2008

Networks---on---Chip (NoCs) have been proposed as a promising solution to the complex on-chip communication problems derived from the increasing number of processor cores. The design of NoCs involves several key issues, being the topological mapping (the mapping of the Intellectual Properties (IPs) to network nodes) one of them. Several proposals have been focused on topological mapping last years, but they require the experimental validation of each mapping considered. In this paper, we propose a communication-aware topological mapping technique for NoCs. This technique is based on the experimental correlation of the network model with the actual network performance, thus avoiding the need…

Computer Science::Hardware ArchitectureComputer scienceNode (networking)Distributed computingNetwork performanceTopological mappingEnergy consumptionNetwork topologyNetwork model
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