Gh. Lazea

Universitatea Tehnica Cluj-Napoca, Klausenburg, Cluj, Romania

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Publications (14)0.54 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.
    No preview · Article · May 2012
  • S. Man · C. Cescon · T. Vieira · S. Herle · Gh. Lazea · R. Merletti
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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.
    No preview · Article · Jan 2011
  • S. Herle · S. Man · Gh. Lazea · C. Marcu · P. Raica · R. Robotin
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    ABSTRACT: Myolectric control is nowadays the most used approach for electrically-powered upper limb prostheses. The myoelectric controllers use electromyographic (EMG) signals as inputs. These signals can be collected from the skin surface using surface EMG sensors, or intramuscular, using needle sensors. No matter which method is used, they have to be processed before being used as controller inputs. In this paper, we present an algorithm based on an autoregressive (AR) model representation and a neural network, for EMG signal classification. The results have shown that combining a low-order AR model with a feed-forward neural network, a rate of classification of 98% can be achieved, while keeping the computational cost low. We also present a hierarchical control architecture and the implementation of the high-level controller using Finite State Machine. The solution proposed is capable of controlling three joints (i.e. six movements) of the upper limb prosthesis. The inputs of the high-level controller are obtained from the classifier, while its outputs are applied as input signals for the low-level controller. The main advantage of the proposed strategy is the reduced effort required to the patient for controlling the prosthetic device, since he only has to initiate the movement that is finalized by the low-level part of the controller.
    No preview · Conference Paper · Jul 2010
  • M. Truşc̆a · Gh. Lazea · A. Fărcaş · P. Dobra · D. Moga
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    ABSTRACT: The implementation of sliding mode control (SMC) for small DC motors is detailed in this paper. Short discussion on sliding mode control theory is made over the case of DC motor modeled under assumptions of load torque as uncertainty. The practical implementation uses the MSP430F2012 controller facilities. Under these considerations, the main result is the fast control loop very efficient for a wide range of DC motor operating conditions. Simulation results and test results using sliding mode control are also presented.
    No preview · Conference Paper · Jun 2010
  • A.L. Majdik · I. Szoke · L. Tamas · M. Popa · Gh. Lazea
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    ABSTRACT: We presents some preliminary results of the ongoing research with the final goal of building an autonomous mobile robot. To achieve this scope the mapping problem is an ineluctable one. This paper presents a visual mapping system which detects the same Speeded Up Robust Features (SURF) on the stereo pair images in order to obtain three dimensional point clouds at every robot location. The algorithm tracks the displacement of the identical features viewed from different positions to get back the robots positions. The Iterative Closest Point (ICP) algorithm is used to register the obtained landmarks in the feature based map of the entire environment. Also a mapping algorithm based on the laser system is presented which can detect the dynamic objects that are present in the robots field. The results of an indoor office environment experiments are shown.
    No preview · Conference Paper · Jun 2010
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    L. Tamas · M. Popa · Gh Lazea · I. Szoke · A Majdik
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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.
    Full-text · Article · Jun 2010 · Control Engineering and Applied Informatics
  • S. Herle · S. Man · Gh. Lazea · C. Marcu · R. Robotin
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    ABSTRACT: Rapid changes on the goods market take place today. These changes require an increased flexibility of the production systems in order to quickly adapt the manufacturing system to a new model of product. However, increasing the flexibility usually also increases the complexity of the system, and therefore the costs per part produced. The challenge is to develop control strategies capable to increase the productivity of a production system, while maintaining the associated costs as low as possible. We propose a control strategy capable of responding to this challenge. Using multitasking programming and optimization of the materials' travel between different points of the flexible manufacturing system, we implement a controller capable to reduce the lead time by up to 26.3%, which leads to an increase of the system's productivity by up to 34%. The control strategy proposed will increase the productivity; moreover no interventions on the hardware systems are required. The strategy also reduces the manufacturing cost per part since the productivity increases.
    No preview · Article · May 2010
  • S. Herle · S. Man · Gh. Lazea · R. Robotin · C. Marcu
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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.
    No preview · Article · May 2010
  • Gh. Lazea · R. Robotin · S. Herle · C. Marcu · L. Tamas
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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.
    No preview · Conference Paper · Jun 2008
  • C. Marcu · Gh. Lazea · R. Robotin · S. Herle · L. Tamas
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    ABSTRACT: This paper presents the conceptual design and the experimental results regarding the development of an industrial robot wireless controller using miniature computers. The industrial robot wireless controller is a part of a bigger project which has as main goal the development of a low-cost industrial robot simulation system. In this paper we describe the general hardware and software architecture of the controller, together with the preliminary experimental results.
    No preview · Conference Paper · Jun 2008
  • L. Tamas · Gh. Lazea · R. Robotin · C. Marcu · S. Herle · Z. Szekely
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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.
    No preview · Conference Paper · Jun 2008
  • M. Trusca · Gh. Lazea · E. Lupu
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    ABSTRACT: The case of an adaptive controller is developed for a robot system actuated by brushed direct current motors in the presence of external disturbances and parametric uncertainties. The control scheme requires the measurements of link position and armature current for feedback. The elaborated adaptive controller results in a closed-loop system locally stable while the all states and signals are bounded and the tracking error can be obtained as small as possible. The advantage of the presented algorithm consists in the number of parameter estimates equal to the number of unknown parameters throughout the entire mechanical system. In consequence, it is eliminated the overparametrization induced by employing the integrator backstepping technique in control of electrically driven robots. Finally, the performance of the proposed approach is illustrated in simulation examples.
    No preview · Conference Paper · Jun 2008
  • S. Herle · Paula Raica · Gh. Lazea · R. Robotin · C. Marcu · L. Tamas
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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.
    No preview · Conference Paper · Jun 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
    No preview · Article · Jan 2006