GUTIÉRREZ SUQUILLO, NELSON RAMIRO

Preferred name
GUTIÉRREZ SUQUILLO, NELSON RAMIRO
Main Affiliation
GISER - Grupo de Investigación en Sistemas Embebidos y Robótica
Web Site
ORCID
0000-0003-2160-528X
Scopus Author ID
57203225105

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    Comparison of Two System Identification Approaches for a Four-Wheel Differential Robot Based on Velocity Command Execution
    (MDPI AG, 2025-06-05)
    GUFFANTI MARTINEZ, DIEGO ANDRES  
    ;
    Moisés Filiberto Mora Murillo
    ;
    Marco Alejandro Hinojosa
    ;
    Santiago Bustamante Sanchez
    ;
    Javier Oswaldo Obregón Gutiérrez
    Precise modeling of differential drive robots is crucial for effective control and trajectory planning in autonomous systems. A comparative analysis of two modeling approaches for a four-wheel differential drive robot is presented in this paper. The first approach, named Motor-Based Model (MBM), identifies four transfer functions, one for each motor, while the second approach, named Simplified Model (SM), uses only two transfer functions, one for linear velocity and another for angular velocity. Both models were validated by comparing their predicted trajectories against real odometry data obtained from a SLAM system implemented on a differential-drive robot. This provided a practical assessment of each model’s accuracy and underscored the importance of model selection in control design and navigation tasks. The results showed that the Motor-Based Model (MBM) consistently outperformed the Simplified Model (SM) in terms of odometry accuracy, both in position and orientation. Across all trajectories, the average RMSE for position using MBM was 0.309 m, while the SM recorded a higher average RMSE of 0.414 m. Similarly, the maximum position error averaged 0.522 m for MBM and 0.710 m for SM, confirming that MBM is more accurate and consistent in position tracking. Regarding the results of orientation estimation, when averaged across all experiments, the MBM maintained a lower angular RMSE of 0.170 rad in contrast to SM, which achieves an RMSE of 0.239 rad. The maximum angular error was also higher for the MBM at 0.316 rad, compared to 0.447 rad for the SM. Moreover, the computational performance evaluation indicated that the SM consistently outperformed MBM, achieving a 30% reduction in simulation time and substantially lower memory usage. These results demonstrate the relationship between model complexity and accuracy and suggest that the motor-specific model is more appropriate for applications requiring precise mapping or localization, such as SLAM, while the simplified model may be suitable for simpler use cases with lower computational requirements, such as embedded systems with limited resources. This paper provides a practical evaluation of the accuracy and computational performance of two modeling approaches, highlighting the implications of model selection for the design of navigation tasks.
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    Control Design and Validation of Gait Analysis with the Robogait Mobile Robotic Platform
    (Springer Nature Switzerland, 2025-09-03)
    GUFFANTI MARTÍNEZ, DIEGO ANDRES  
    ;
    Alberto Brunete
    ;
    Miguel Hernando Gutierrez
    ;
    David Álvarez
    ;
    GUTIÉRREZ SUQUILLO, NELSON RAMIRO  
    The integration of mobile robotic platforms with depth sensors could led to a major advance in human gait analysis. However, the lack of dedicated technologies designed specifically for corridor-based gait analysis limits the availability of comprehensive tools to accurately and efficiently capture and analyze gait data in this specific context. In this study, control algorithms for person following and lane keeping of a mobile robotic platform named Robogait were applied and validated experimentally. The validity of using an Azure Kinect sensor for gait analysis was also examined using gait data collected from 10 participants and comparing its accuracy in gait signals and gait parameters with respect to a Vicon photogrammetric system. Results in controller design demonstrated a path following error of only 0.0446 m was measured on average, with a maximum deviation of 0.1420 m. The person tracking presented slight oscillations, however it did not affect the performance of the system in the gait analysis. An RMSE error of 12.68 was obtained for knee flex./ext., 5.54 for hip flex./ext., and just 0.06 m for the inter-ankle distance. Regarding gait descriptors analyzed, the Azure Kinect system provides reliable gait event measurements, though some discrepancies exist compared to Vicon. This study validates the use of the Azure Kinect sensor in gait analysis with mobile platforms. This offers a low-cost solution in real environments such as hospital corridors, contrary to in-lab gait analysis where the influence of equipment and the controlled environment could alter the gait pattern. The robot setup errors were comparable to static treadmill systems and similar to those of Vicon systems, which highlights its potential in clinical and rehabilitation applications.
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    Optimization of Fault Prediction by A.I. in Industrial Equipment: analysis of the operating parameters of a Bench Grinder
    (AG Editor (Argentina), 2025-03-18)
    GUTIERREZ SUQUILLO, NELSON RAMIRO  
    ;
    CHAMBA CRUZ, JONNATHAN ISMAEL  
    ;
    Christiam Xavier Núñez
    ;
    SANCHEZ MUYULEMA, LUIS MIGUEL  
    ;
    Rafael Christian Franco Reina
    Predictive Maintenance (PM) plays a crucial role in maximizing efficiency and reducing costs associated with equipment and system maintenance in industrial companies. Recent advancements in Machine Learning (ML) have revolutionized PM by offering accurate and efficient fault prediction and maintenance planning capabilities. This research focuses on monitoring a bench grinder and observing sensors for temperature, current, angular velocity, and vibration under normal operating conditions. The objective is to predict failures based on specific variables related to the machine. To develop the system, a prototype bench was designed to subject the machine to several working scenarios, collecting real-time sensor data. Data clusters were generated for each sensor, collecting 3000 samples over 7 consecutive days without faults and another 7 days with modified bench grinder behavior. Sampling was done at a rate of 1 second. The performance of Decision Trees (DT), Support Vector Machines (SVM), Naive Bayes (NB), and K-Means + Neural Network (NN) algorithms was compared using the confusion matrix metrics. Each algorithm's performance was evaluated for RPM, current, temperature, and vibrations measures. The SVM algorithm showed the highest error for RPM with 43.5%. In contrast, all algorithms achieved minimal or zero errors for vibrations, indicating excellent performance. These findings demonstrate the potential of ML algorithms in PM for the bench grinder. The results highlight the importance of selecting appropriate algorithms for specific measurements, with vibrations exhibiting the least error across all algorithms and contributes to optimize maintenance activities in industrial settings.
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    Application of Model-Based Design for Filtering sEMG Signals Using Wavelet Transform
    (AG Editor (Argentina), 2025-02-13)
    Vladimir Bonilla Venegas
    ;
    Guillermo Mosquera Canchingre
    ;
    Miguel Sánchez Muyulema  
    ;
    Jonnathan Ismael Chamba Cruz
    ;
    Nelson Gutiérrez Suquillo  
    The aim of this study was the integration of model-based design and Wavelet transform techniques for filtering surface electromyography (sEMG) signals. In the first stage the noises and interferences that disturb sEMG signals were analyzed to implement a digital filter in a low-cost embedded system that filters these signals. It was shown that the noises and interferences are caused by various sources. Sources of interference and noise can be divided into internal and external. Internal noise is caused by the electrodes, EMG signals of other muscles, and noise associated with the functioning of other organs such as the heart or stomach. The external noises are due to the electrical environment, the most prominent of which is the direct interference of the power hum, produced by the incorrect grounding of other devices and electromotors. For the analysis of the digital filter, sEMG signals from the biceps muscle were used when the elbow joint was at rest and during flexion and extension movements. Signals from 10 participants who did not have any atrophies or pathologies in the muscle were considered for this stage. Denoising of sEMG signals was performed using different wavelets; the smallest error was observed when using the biorthogonal wavelet 3/5 of level 6 with the soft thresholding method. The wavelet filter was implemented using the V-model, and the Processor in The Loop (PIL) tests helped to determine the characteristics of the embedded system where the digital filter was implemented. The digital filter code was implemented on an ESP32 board due to its processing speed of 328 ms.
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    Analysis by the Finite Element Method of the Behavior of the Brake Pads Using CAE Software
    (IEEE, 2017-11)
    Alexy Fabian Vinueza Lozada
    ;
    GUTIERREZ SUQUILLO, NELSON RAMIRO  
    The study of the behavior of the brake pads of an ABS breaking system with different materials was done through the Finite Element Analysis Method using software tools. The necessary steps to carry out the study were: determine the specifications, requirements and restrictions, type of analysis and physical variables to be studied as well as the mathematical model. From this information the modeling of the system, discretization (mesh), establishment of the boundary conditions and finally resolution of the problem, generation of results and Post processing were made. It is fundamental to realize a quality mesh so that this allows to improve the convergence of results by optimizing the computational load so that the problem can be solved. One of the most useful questions of this method is that in the post-processing stage, figures, curves and tables can be generated providing a wide range of results, the person doing the study determining which is the most relevant information for each case. In this work, temperature, heat flow, stress, strain and energy dissipated by the braking process were obtained.