Gh. Lazea

Universitatea Tehnica Cluj-Napoca, Cluj-Napoca, Judetul Cluj, Romania

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Publications (8)0 Total impact

  • C. Marcu, S. Herle, L. Tamas, Gh. Lazea
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    ABSTRACT: This paper presents a video based control system for a Fanuc M-6iB/2HS articulated robot. The system uses a CMUCam3 video camera connected to PC. The industrial robot is controlled via the TCP/IP protocol using a custom simulation software created in previous researches for the industrial robot. The simulation software implements additional classes designed to control and monitor the video camera. The paper presents in detail the calibration and testing stages. The system is capable to detect cylindrical objects of any stored color and is able to determine their position in the working space of the robot.
    01/2012;
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    ABSTRACT: The classification of electromiographic signals provides a method to identify one's intent or movement. This paper presents a study on choosing the best model for a classifier used to group electromiographic signals into classes corresponding to the isometric flexion effort of different fingers. The signals were collected from the Flexor Digitorum Superficialis and Profundus of seven healthy subjects. Different features (root mean square -RMS, average rectified value - ARV, mean and median frequency) and different classifier structures (discriminant analysis, nearest neighbor analysis, naive Bayes algorithm, neural network, fuzzy logic based algorithm) were implemented with classification success rates ranging from 50 to 99 %. The success rate of the classifiers corresponds to the ability of a numerical system to decode the physiological manifestations associated with the finger movements.
    01/2011;
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    ABSTRACT: Most electrically powered upper limb prostheses are myoelectrically controlled. The myoelectric controllers use surface electromyographical signals as inputs. These signals, collected from the surface of the skin, have to be preprocessed before being used as inputs for the controller. In this paper we present a classifier for surface electromyographical signals based on an autoregressive (AR) model representation and a neural network, and the higher level of the hierarchical controller implemented using Finite State Machine. The results had shown that using a low order autoregressive model combined with feed forward neural networks achieves a rate of classification of 91% while keeping the computational cost low. Using the hierarchical controller, the necessary effort to control the prosthesis by the patient is reduced since the patient only have to initiate the movement which is finalized by the low level part of the controller. The inputs of the high level controller are obtained from the classifier. The outputs of the high level controller are applied as inputs to the low level controller.
    International Conference on Automation, Quality and Testing, Robotics. 01/2010; 2:1-6.
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    ABSTRACT: This paper presents a multi-sensor architecture to detect moving persons based on the information aquired from a lidar and vision systems. The detection of the objects are performed relative to the estimated robot position. For the lidar the Gaussian Mixture Model (GMM) classifier and for the vision the AdaBoost classifier is used from which the outputs are combined with the Bayesian rule. The estimated person positions are tracked via the Extended Kalman filter. The main aim of the paper was to reduce the false positives in the detection process with the use of a sequentially combined classifiers.
    Journal of Control Engineering and Applied Informatics. 01/2010; 12(2):30-35.
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    ABSTRACT: The aim of this paper is to present concepts and algorithms for formation navigation in multi-mobile robots systems. The behavior based approach was chosen considering a correspondence with biological systems. The paper presents aspects concerning absolute and relative mobile robots positioning within a formation, as well as inter-robot communication using a client-server model and TCP/IP protocol. The simulations and real-world experiments with Pioneer mobile robots led to results backing up the theoretical part.
    Automation, Quality and Testing, Robotics, 2008. AQTR 2008. IEEE International Conference on; 06/2008
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    ABSTRACT: The development of a training system in the field of rehabilitation has always been a challenge for scientists. Surface electromyographical signals are widely used as input signals for upper limb prosthetic devices. The great mental effort of patients fitted with myoelectric prostheses during the training stage, can be reduced by using a simulator of such device. This paper presents an architecture of a system able to assist the patient and a classification technique of surface electromyographical signals, based on neural networks. Four movements of the upper limb have been classified and a rate of recognition of 96.67% was obtained when a reduced number of features were used as inputs for a feed-forward neural network with two hidden layers.
    Automation, Quality and Testing, Robotics, 2008. AQTR 2008. IEEE International Conference on; 06/2008
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    ABSTRACT: This paper tackles the problem of the position measurement and estimation techniques in the robot navigation field based on Kalman filters. It presents the problem of the position estimation based on odometric, infrared and ultrasonic measurements. Further on deals with the theoretical and practical aspects of the state estimation based on Kalman filtering techniques. From the wide range of derivatives of the Kalman filtering technique there are detailed the Extended Kalman filter and the one based on Unscented Transformation. In the second part of the paper is concluded with the results of the comparison between the different filtering algorithms and the further perspectives regarding this subject.
    Automation, Quality and Testing, Robotics, 2008. AQTR 2008. IEEE International Conference on; 06/2008
  • C. Marcu, Gh. Lazea, R. Robotin
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    ABSTRACT: This paper presents a Visual C++ and OpenGL application for 3D simulation of the serial industrial robots. To develop this application we started from the forward kinematics of the robot taken into consideration. The functions implemented in the source code are able to calculate the position and orientation of each robot joint, including the position and orientation of the robot gripper. With the help of the OpenGL functions, the application is able to draw and simulate the 3D kinematic scheme of the robot. In addition, the application has a calculus module where the gripper position can be determined using particular values for the robot joints positions or orientations
    International Conference on Automation, Quality and Testing, Robotics. 01/2006; 2:254-259.