Search results for "Computer Science - Robotics"

showing 7 items of 7 documents

Compensation of compliance errors in parallel manipulators composed of non-perfect kinematic chains

2012

The paper is devoted to the compliance errors compensation for parallel manipulators under external loading. Proposed approach is based on the non-linear stiffness modeling and reduces to a proper adjusting of a target trajectory. In contrast to previous works, in addition to compliance errors caused by machining forces, the problem of assembling errors caused by inaccuracy in the kinematic chains is considered. The advantages and practical significance of the proposed approach are illustrated by examples that deal with groove milling with Orthoglide manipulator.

FOS: Computer and information sciences0209 industrial biotechnologyComputer sciencenonlinear stiffness modelingcompliance error compensation02 engineering and technologyKinematicsCompensation (engineering)Computer Science::RoboticsComputer Science - Robotics020901 industrial engineering & automation0203 mechanical engineeringMachiningControl theorymedicine[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]ManipulatorGroove (engineering)Parallel manipulatorStiffnessparallel robots020303 mechanical engineering & transportsTrajectorymedicine.symptomnon-perfect manipulatorsRobotics (cs.RO)
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Distributed and proximity-constrained C-means for discrete coverage control

2018

In this paper we present a novel distributed coverage control framework for a network of mobile agents, in charge of covering a finite set of points of interest (PoI), such as people in danger, geographically dispersed equipment or environmental landmarks. The proposed algorithm is inspired by C-Means, an unsupervised learning algorithm originally proposed for non-exclusive clustering and for identification of cluster centroids from a set of observations. To cope with the agents' limited sensing range and avoid infeasible coverage solutions, traditional C-Means needs to be enhanced with proximity constraints, ensuring that each agent takes into account only neighboring PoIs. The proposed co…

FOS: Computer and information sciences0209 industrial biotechnologyControl and OptimizationComputer scienceDistributed computing02 engineering and technologyIndustrial and Manufacturing EngineeringSet (abstract data type)Disaster reliefComputer Science - Robotics020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringDecision Sciences (miscellaneous)Cluster analysisData fusion processPoints of interest(poi)Sensing rangesNon-exclusive clusteringData fusionDisaster preventionSensor fusionEuclidean distanceCoverage controlIdentification (information)Range (mathematics)Information concerningRanking020201 artificial intelligence & image processingMobile agentsRobotics (cs.RO)Cluster centroids
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Compliance error compensation technique for parallel robots composed of non-perfect serial chains

2012

The paper presents the compliance errors compensation technique for over-constrained parallel manipulators under external and internal loadings. This technique is based on the non-linear stiffness modeling which is able to take into account the influence of non-perfect geometry of serial chains caused by manufacturing errors. Within the developed technique, the deviation compensation reduces to an adjustment of a target trajectory that is modified in the off-line mode. The advantages and practical significance of the proposed technique are illustrated by an example that deals with groove milling by the Orthoglide manipulator that considers different locations of the workpiece. It is also de…

FOS: Computer and information sciences0209 industrial biotechnologyEngineeringGeneral Mathematicsnonlinear stiffness modelingcompliance error compensation02 engineering and technologyIndustrial and Manufacturing EngineeringCompensation (engineering)Computer Science::RoboticsSuperposition principleComputer Science - Robotics020901 industrial engineering & automation0203 mechanical engineeringControl theorymedicine[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]ManipulatorGroove (engineering)business.industryMode (statistics)Parallel manipulatorStiffnessComputer Science Applications020303 mechanical engineering & transportsControl and Systems EngineeringTrajectoryParallel robotsmedicine.symptombusinessnon-perfect manipulatorsRobotics (cs.RO)Software
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Using Hankel matrices for dynamics-based facial emotion recognition and pain detection

2015

This paper proposes a new approach to model the temporal dynamics of a sequence of facial expressions. To this purpose, a sequence of Face Image Descriptors (FID) is regarded as the output of a Linear Time Invariant (LTI) system. The temporal dynamics of such sequence of descriptors are represented by means of a Hankel matrix. The paper presents different strategies to compute dynamics-based representation of a sequence of FID, and reports classification accuracy values of the proposed representations within different standard classification frameworks. The representations have been validated in two very challenging application domains: emotion recognition and pain detection. Experiments on…

FOS: Computer and information sciencesComputer Science - Artificial IntelligenceComputer Vision and Pattern Recognition (cs.CV)Speech recognitionFeature extractionComputer Science - Computer Vision and Pattern RecognitionPainLTI system theoryComputer Science - RoboticsLinear time invariant systemRepresentation (mathematics)Hidden Markov modelMathematicsEmotionSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSequencebusiness.industryPattern recognitiondynamicsClassificationSupport vector machineArtificial Intelligence (cs.AI)Face (geometry)Artificial intelligencebusinessRobotics (cs.RO)Hankel matrix2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Ensemble of Hankel Matrices for Face Emotion Recognition

2015

In this paper, a face emotion is considered as the result of the composition of multiple concurrent signals, each corresponding to the movements of a specific facial muscle. These concurrent signals are represented by means of a set of multi-scale appearance features that might be correlated with one or more concurrent signals. The extraction of these appearance features from a sequence of face images yields to a set of time series. This paper proposes to use the dynamics regulating each appearance feature time series to recognize among different face emotions. To this purpose, an ensemble of Hankel matrices corresponding to the extracted time series is used for emotion classification withi…

FOS: Computer and information sciencesComputer Science - RoboticsComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputer Science - Human-Computer InteractionRobotics (cs.RO)Human-Computer Interaction (cs.HC)
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Safety assurance of an industrial robotic control system using hardware/software co-verification

2022

As a general trend in industrial robotics, an increasing number of safety functions are being developed or re-engineered to be handled in software rather than by physical hardware such as safety relays or interlock circuits. This trend reinforces the importance of supplementing traditional, input-based testing and quality procedures which are widely used in industry today, with formal verification and model-checking methods. To this end, this paper focuses on a representative safety-critical system in an ABB industrial paint robot, namely the High-Voltage electrostatic Control system (HVC). The practical convergence of the high-voltage produced by the HVC, essential for safe operation, is f…

FOS: Computer and information sciencesFormal Languages and Automata Theory (cs.FL)Formal methodsVerificationComputer Science - Formal Languages and Automata Theory:Teknisk kybernetikk: 553 [VDP]VDP::Teknisk kybernetikk: 553RoboticsComputer Science - RoboticsVDP::Technical cybernetics: 553:Technical cybernetics: 553 [VDP]VerifikasjonFormelle metoderRobotikkRobotics (cs.RO)Software
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RGB-Event Fusion for Moving Object Detection in Autonomous Driving

2022

Moving Object Detection (MOD) is a critical vision task for successfully achieving safe autonomous driving. Despite plausible results of deep learning methods, most existing approaches are only frame-based and may fail to reach reasonable performance when dealing with dynamic traffic participants. Recent advances in sensor technologies, especially the Event camera, can naturally complement the conventional camera approach to better model moving objects. However, event-based works often adopt a pre-defined time window for event representation, and simply integrate it to estimate image intensities from events, neglecting much of the rich temporal information from the available asynchronous ev…

FOS: Computer and information sciences[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Computer Science - Robotics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Computer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognition[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Robotics (cs.RO)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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