J.C. Pedraza-Ortega

5-DOF manipulator simulation based on MATLAB-Simulink methodology

This work presents a novel simulation methodology applied to a 5-DOF manipulator. The work includes mathematical modeling of the direct, inverse and differential kinematics as well as the dynamics of the manipulator. The method implements the path following in the 3D space and uses the Matlab-Simulink approach. Several paths were tested to verify the method. This methodology can be used with different robots to test the behavior and control laws.

Comparison between Fuzzy C-means clustering and Fuzzy Clustering Subtractive in urban air pollution

Clustering is generally associated with classification problem. In this contribution, the implementation of cluster estimation method as a basis of a fuzzy model identification algorithm has been developed. A comparison between two different clustering techniques is presented, Fuzzy C-means clustering and Fuzzy Clustering Subtractive. Also, an application in modeling the relationship between temperature, humidity and PM10 concentration in urban air pollution in Liverpool at northwest of England is presented.

Performance assessment of fuzzy clustering models applied to urban airborne pollution

An application in modeling a non-lineal system between temperature, humidity and urban airborne air pollution is presented. In this contribution, the implementation of cluster estimation method as a basis of a fuzzy model identification algorithm has been developed. Fuzzy clustering allowed partitioning this complex non-linear system into many linear sub-systems. Finally, comparison of the performance between two different clustering techniques for this particular case study is presented: Fuzzy C-means Clustering and Fuzzy Subtractive Clustering.

A comparison between local and global phase unwrapping algorithms in a modified Fourier Transform Profilometry Method

This work present a modified Fourier Transform Profilometry method, in particular, the development of local and global phase unwrapping algorithms has been considered, because this is one of the major challenges when this method is applied. The basic idea is to project a sinusoidal fringe pattern with a known spatial frequency on the object to digitize, and then a vision system captures and processes the image to obtain the objects depth information. First, the fringe pattern is projected on a reference plane then an image is acquired, later the object to digitize is placed in front of the reference plane and then another image is acquired. The fringe pattern is distorted due to the objects irregular shape. One of the main difficulties to face is the high frequency content in the unwrapping process. This effect can be minimized by knowing the spatial frequency and its multiples. Here, we propose to implement global and local phase unwrapping algorithms to overcome the high frequency problems. These algorithms are part of the modified Fourier Transform Profilometry Method (FTP), where the resulting phase difference of the acquired and processed images have the information of the objects depth. Some tests with computer generated and real objects with different geometries are carried out to verify the proposed methodology, considering the factors that mostly affect the method.

Fuzzy logic hardware implementation for pneumatic control of one DOF pneumatic robot

The pneumatic actuators can be a useful way to control the position of a manipulator robot, instead of an electrical actuator. The major problem with pneumatic actuators is the compressibility of the air, due to the fact that the mathematical model is a system formed by a set of highly non-linear equations then a simple PID control is not enough to control the robot position, and fuzzy logic is a good option. This work is focused on the hardware implementation of Fuzzy logic algorithm into FPGA system. This paper also presents a methodology to implement a pneumatic control using fuzzy logic, into a FPGA device, which is the main contribution of this work. The air flow is controlled with a pulse width modulation, applied to the pneumatic electro- valve, with 25 ms of period.

Image dehazing using morphological opening, dilation and Gaussian filtering

Image pre-processing is a critical stage in computer vision systems, with greater relevance when the input images are captured in outdoor environments because the pictures could contain low contrast and modified colors. A common condition present in outdoor images is haze. In this work, a new dehazing algorithm based on dark channel prior mathematical morphology operations (opening and dilation), and a Gaussian filter, is proposed. Moreover, the proposed algorithm performance is compared qualitatively and quantitatively against previously reported algorithms. Obtained results show that the proposed algorithm requires less processing time providing higher quality dehazing results than other state-of-the-art approaches.

Feature Extraction of EEG Signal upon BCI Systems Based on Steady-State Visual Evoked Potentials Using the Ant Colony Optimization Algorithm

This work presents the use of swarm intelligence algorithms as a reliable method for the optimization of electroencephalogram signals for the improvement of the performance of the brain interfaces based on stable states visual events. The preprocessing of brain signals for the extraction of characteristics and the detection of events is of paramount importance for the improvement of brain interfaces. The proposed ant colony optimization algorithm presents an improvement in obtaining the key features of the signals and the detection of events based on visual stimuli. As a reference model, we used the Independent Component Analysis method, which has been used in recent research for the removal of nonrelevant and detection of relevant data from the brain’s electrical signals and also allows the collection of information in response to a stimulus and separates the signals that were generated independently in certain zones of the brain.

New Strategy to Approach the Inverse Kinematics Model for Manipulators with Rotational Joints

The chapter describes a new strategy to approach the solution of the inverse kinematics problem for robot manipulators. A method to determine a polynomial model approximation for the joints positions is described by applying the divided differences with a new point of view for lineal path in the end-effector of the robot manipulator. Results of the mathematical approach are analysed by obtaining the kinematics inverse model and the approximate model for lineal trajectories of a manipulator for three degrees of freedom. Finally, future research approaches are commented.

HTG-Based Kinematic Modeling for Positioning of a Multi-Articulated Wheeled Mobile Manipulator

This paper presents a novel methodology for positioning an explosive ordnance device (EOD) which consists of a mobile manipulator with 12° of freedom. The approach uses an extension of a homogeneus transformation graph (HTG) which can be used in the kinematic modeling of mobile manipulators and unmanned aerial vehicles. In this approach the complete kinematics is modeled as one unit in contrast to previous approaches where the manipulator and mobile body are decoupled. The system is tested in several escenarios (simulated and real experimentation) like approaching to an explosive device location on the plane as well as in slope ways, climbing stairs, lifting itself and manipulating procedures. All the aforementioned scenarios were developed using the HTG which establishes the appropriate transformations and interaction parameters of the coupled system. Finally, the system is tested (simulated and real experimentation) for positioning its end device in a target with a RMS positioning average error ofr 7.91 mm which is acceptable for this kind of devices.