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Guijarro M,Complutense University of Madrid | Pajares G.,Complutense University of Madrid | Riomoros I.,Complutense University of Madrid | Herrera P.J,Complutense University of Madrid | And 2 more authors.
Computers and Electronics in Agriculture | Year: 2011

One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevant image processing procedures require the identification of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-specific treatments with chemical products or mechanical manipulations. Also the identification of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on specific areas. This implies that the images to be processed contain textures of three main types to be identified: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to refine the identification of sub-textures inside the main ones. Concerning the green identification, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; finally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third finding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processing. © 2010 Elsevier B.V.


Gajate A.,Institute Automatica Industrial | Haber R.E.,Institute Automatica Industrial | Haber R.E.,Autonomous University of Madrid | Del Toro R.M.,Institute Automatica Industrial
International Journal of Innovative Computing, Information and Control | Year: 2010

This paper reports on the design and implementation of a neurofuzzy system for modelling and controlling drilling processes in an Ethernet-based application. The neurofuzzy system in question is an Adaptive Network based Fuzzy Inference System (ANFIS), where fuzzy rules are obtained from input/output data. The design of the control system is based on the internal model control paradigm. The main advantages of the suggested approach are that its use of a neurofuzzy system to deal with nonlinear drilling process behaviour and process uncertainty eliminates the need for an exact mathematical model to design and tune the control system, and that it offers a simple and computationally efficient procedure for real-time applications. The results are positive in both simulation and in the real-time application of networked control. The case study indicates that the proposed method outperforms a PID control strategy and an optimal fuzzy controller. This improved behaviour is verified by several performance indices. © 2010 ISSN.


Abellanas A.,Institute Automatica Industrial | Frizera A.,Institute Automatica Industrial | Ceres R.,Institute Automatica Industrial | Gallego J.A.,Institute Automatica Industrial
Sensors and Actuators, A: Physical | Year: 2010

Walkers are designed to assist pathological gait by providing weight support, assisting balance and enhancing rehabilitation, as they rely on user's ability to walk. Nevertheless, it is important to continuously obtain certain gait parameters (i) to characterize gait patterns, (ii) to perform follow up and improve rehabilitation strategies and (iii) to efficiently and safely control the device. Due to usability issues and for a broad analysis of gait, it is essential to design sensor architectures that avoid user preparation or environmental instrumentation. In this paper, we present a measurement system for the precise detection of Heel-Strike (HS) and Toe-Off (TO) and for continuous cadence estimation and tracking based on force interaction between user's upper-body and walker handles. HS and TO estimation methods present mean errors of 1.35 and 0.55% respect to gait cycle. For continuous cadence estimation, the Mean Square Error is below 3.3 steps per minute. © 2010 Elsevier B.V. All rights reserved.


Vallejo A.J.,Institute Automatica Industrial | Morales-Menendez R.,Monterrey Institute of Technology | Ramirez-Mendoza R.,Monterrey Institute of Technology | Garza-Castanon L.,Monterrey Institute of Technology
2009 European Control Conference, ECC 2009 | Year: 2015

An online surface roughness prediction module for peripheral end milling in High Speed Machining was developed. An Artificial Neural Network framework integrated five cutting parameters and one process variable signal. Vibration signal in the workpiece showed high correlation with the surface roughness. This signal was pre-processed as Mel Frequency Cesptrum Coefficients. This could be a practical solution for a wide cutting conditions with several Aluminium alloys and cutting tools. Results were validated by using an industrial High Speed Machining center. © 2009 EUCA.


Vallejo A.J.,Institute Automatica Industrial | Morales-Menendez R.,Monterrey Institute of Technology
Annual Reviews in Control | Year: 2010

A proposal for an intelligent monitoring and control system is introduced. Achievement of a specific surface roughness is themain goal because it is a well-known index of product quality and a technical requirement for mechanical products. The system integrates four modules: Data acquisition, surface roughnessmonitoring, cutting toolmonitoring, and intelligent process planning. Values of the cutting parameters for a peripheral milling process are estimated a priori, and by using aGeneticAlgorithm, the optimal cutting parameters are determined. In intelligent process planning module, aMarkov decision process is implemented to compute an optimal machining policy. Based on this policy, the system generates recommendations that optimize the operating costs. © 2009 Elsevier Ltd.


Martin C.J.,Institute Automatica Industrial | Martinez-Graullera O.,Institute Automatica Industrial | Godoy G.,Escuela Polytechnic Superior | Ullate L.G.,Institute Automatica Industrial
IEEE Transactions on Image Processing | Year: 2010

Synthetic aperture (SA) techniques have been frequently used to reduce the volume and complexity of the imaging systems. A useful tool for designing synthetic aperture configurations is the coarray. This is the virtual aperture that produces in one way the same beam pattern as the SA system in emission and reception. In this correspondence, we propose a new algorithm, based on the polynomial decomposition, that allows to obtain any wanted coarray on a linear array using whatever synthetic aperture configuration. With this fast and simple algorithm, the desired coarray is decomposed into a set of sub-apertures, whose length is determined by the requirements and resources of the system. The result is the set of weights that have to be applied on the sub-apertures to get the desired coarray, and consequently, the wanted beam pattern. © 2006 IEEE.


Brizuela J.,Institute Automatica Industrial | Ibanez A.,Institute Automatica Industrial | Fritsch C.,Institute Automatica Industrial
Journal of Systems Architecture | Year: 2010

A special NDE system built into a low-cost FPGA has been developed for detecting railway wheelflats. The system operates with the train moving at low-speed over a measuring rail. Ultrasonic surface wave pulses are sent at regular intervals and echoes are acquired and processed by the system. The variations in the round trip time-of-flight (RTOF) of the ultrasonic pulse allow to detect and quantify the flats size. The logic design optimizes the storage capabilities by keeping only the rail-wheel contact echo and its environment. For this purpose, a wheel tracking algorithm has been implemented. It allows reducing the data volume by controlling the delay time from pulse emission to the acquisition window following the running wheel. Furthermore, since signals are masked by the rail structural noise, they are processed before executing the tracking algorithm. This work presents the architecture and performance of the developed system with experimental data. © 2010 Elsevier B.V. All rights reserved.


Milanes V.,Institute Automatica Industrial | Perez J.,Institute Automatica Industrial | Onieva E.,Institute Automatica Industrial | Gonzalez C.,Institute Automatica Industrial
IEEE Transactions on Intelligent Transportation Systems | Year: 2010

A major research topic in intelligent transportation systems (ITSs) is the development of systems that will be capable of controlling the flow of vehicular traffic through crossroads, particularly in urban environments. This could significantly reduce traffic jams, since autonomous vehicles would be capable of calculating the optimal speed to maximize the number of cars driving through the intersection. We describe the use of vehicle-to-vehicle (V2V) communications to determine the position and speed of the vehicles in an environment around a crossroad. These data are used to estimate the intersection point, and a fuzzy controller then modifies the speed of the cars without right of way according to the speed of the car with right of way. Experimental tests conducted with two mass-produced cars on a real circuit at the facilities of the Instituto de Automtica Industrial, Consejo Superior de Investigaciones Cientficas, Madrid, Spain, gave excellent results. © 2010 IEEE.


Brizuela J.,Institute Automatica Industrial | Ibanez A.,Institute Automatica Industrial | Nevado P.,Institute Automatica Industrial | Fritsch C.,Institute Automatica Industrial
Physics Procedia | Year: 2010

A new inspection system for railway wheels using the Doppler Effect is presented in this work. The proposed system analyses the rail-wheel contact by frequency and phase shifts. Cracks on the wheel tread are determined while the train moves at a low speed. A special rail is used to propagate monochromatic surface waves. When a wheel on the measuring rail moves at constant speed, the received signal will present a regular frequency shift related with the movement speed. The difference between the emitted and the received frequencies will change if any defect on the wheel tread is detected.


Guevara J.,Institute Automatica Industrial | Jimenez A.R.,Institute Automatica Industrial | Morse A.S.,Yale University | Fang J.,Yale University | And 2 more authors.
IEEE International Symposium on Industrial Electronics | Year: 2010

This paper studies the problem of determining the position of beacon nodes in Local Positioning Systems, for which there is no inter-node distance measurements available. Also, neither the mobile node nor any of the stationary nodes have positioning or odometry information. The common solution is implemented using a mobile node capable of measuring its distance to the stationary beacon nodes within a sensing radius. Many authors had implemented heuristic methods based on optimization algorithms to solve the problem, however such techniques can fail if the range measurements doesn't provide enough information to obtain a unique solution. Equally, the actual methods require a good initial estimation of the node positions in order to find the correct solution. In this paper we use rigidity theory to determine the necessary conditions in which such problem is solvable for Local Positioning Systems. We also a present a new method to calculate the inter-beacon distances based in the linearization of the trilateration equations. This method doesn't require any initial estimation of the nodes position. The simulation results show a good estimation of the beacon nodes position without using any optimization algorithm. © 2010 IEEE.

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