Moya-Albor, Ernesto
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Moya-Albor, Ernesto
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Moya Albor, Ernesto
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emoya
Moya-Albor, E.
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55523223700
Researcher ID
J-1891-2019

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Now showing 1 - 10 of 69
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Distributed evolutionary learning control for mobile robot navigation based on virtual and physical agents

2020 , Ponce, Hiram , Moya-Albor, Ernesto , Martinez-Villaseñor, Lourdes , Brieva, Jorge

This paper presents a distributed evolutionary learning control based on social wound treatment for mobile robot navigation using an integrated multi-robot system comprised of simulated and physical robots. To do so, this work proposes an extension of the population-based metaheuristic wound treatment optimization (WTO) method into a distributed scheme. In addition, this distributed WTO method is implemented on the multi-robot system allowing them to experience the environment in their own and communicate their findings, resulting in an emergence intelligence. We implemented our proposal using the combination of five simulated robots with one physical robot for tuning a navigation controller to move freely in a workspace. Results showed that the solution found by this multi-robot system aims using the output controller in the physical robot for successfully achieving the goal to move the robot around a U-maze, without applying any transfer learning approach. We consider this proposal useful in evolutionary robotics, and of great importance to decrease the gap related to transfer knowledge in robotics from simulation to reality. © 2019 Elsevier B.V.

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Mechatronic Design of a Low-Cost Smart Wheelchair Controlled by Joystick and Voice Commands

2023 , Bobadilla-Rendón, David , Monroy-Rueda de León, Irvine J. , Salazar-Salinas, Gabriel , Stefan-Lepe De Soto, Antonio , Ponce, Hiram , Moya-Albor, Ernesto , Brieva, Jorge

Elderly people have increased at an accelerated rate in recent years. In Mexico, one of the main problems affecting this population are related to disabilities, specifically limited mobility, i.e., arthritis in older adults. Different technological solutions have been proposed, such as electrical wheelchairs. However, for arthritic people, these wheelchairs are difficult to operate, lacking comfortability, and might be very expensive. In this work, we propose the development of a smart wheelchair for arthritic older adults able to move automatically and controlled by using slight manual movements of the hand and by voice commands. We followed the general methodology of a mechatronic design. A proof-of-concept model of the wheelchair was implemented. For validation, we tested the prototype in different real indoor scenarios. Results conclude that our proposed smart wheelchair complies with the user requirements, it is easy to operate, and the cost is reduced considerably. We anticipate this is a low-cost efficient smart wheelchair prototype that can be further considered for real technological solutions.

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Segmentation and optical flow estimation in cardiac CT sequences based on a spatiotemporal PDM with a correction scheme and the Hermite transform

2016 , Barba-J., Leiner , Moya-Albor, Ernesto , Escalante-Ramírez, Boris , Brieva, Jorge , Vallejo Venegas, Enrique

Purpose: The left ventricle and the myocardium are two of the most important parts of the heart used for cardiac evaluation. In this work a novel framework that combines two methods to isolate and display functional characteristics of the heart using sequences of cardiac computed tomography (CT) is proposed. A shape extraction method, which includes a new segmentation correction scheme, is performed jointly with a motion estimation approach.Methods: For the segmentation task we built a Spatiotemporal Point Distribution Model (STPDM) that encodes spatial and temporal variability of the heart structures. Intensity and gradient information guide the STPDM. We present a novel method to correct segmentation errors obtained with the STPDM. It consists of a deformable scheme that combines three types of image features: local histograms, gradients and binary patterns. A bio-inspired image representation model based on the Hermite transform is used for motion estimation. The segmentation allows isolating the structure of interest while the motion estimation can be used to characterize the movement of the complete heart muscle.Results: The work is evaluated with several sequences of cardiac CT. The left ventricle was used for evaluation. Several metrics were used to validate the proposed framework. The efficiency of our method is also demonstrated by comparing with other techniques.Conclusion: The implemented tool can enable physicians to better identify mechanical problems. The new correction scheme substantially improves the segmentation performance. Reported results demonstrate that this work is a promising technique for heart mechanical assessment. © 2016 Elsevier Ltd.

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Design of a Soft Gripper Hand for a Quadruped Robot

2023 , Benavente González, Javier , Poza, José , Robles, Jacobo , Ponce, Hiram , Brieva, Jorge , Moya-Albor, Ernesto

This work aims to solve a current balancing problem for a quadruped robot by proposing a soft gripper. The main problem for the project is the lack of modules to make a quadruped robot walk through tough environments, which is designed to help in accidents to look for people and maintenance in factories. Viable solutions for the main body were found with a look alike chameleon robot. With that premise, the goal for the chameleon robot is to have a capable of moving through difficult surfaces and to have enough movement so to get better results in the displacement. To fulfill this requirement, the proposed key idea presented here is to design a gripper capable of helping the main body to achieve difficult places being as safe as possible. Furthermore, the gripper is an actual module for the main robot, and should be easy to substitute and build, in case it is needed in other situations. Because of that, the gripper is designed with the help of soft robotics. Experimental results in lab show the effectiveness of the soft gripper. We anticipate this system will help the robot to use the force effectively through each step. © 2023 IEEE.

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Image Encryption and Decryption System through a Hybrid Approach Using the Jigsaw Transform and Langton’s Ant Applied to Retinal Fundus Images

2021 , Romero Arellano, Andrés Gabriel , Moya-Albor, Ernesto , Brieva, Jorge , Cruz-Aceves, Ivan , Avina-Cervantes, Juan Gabriel , Hernandez-Gonzalez, Martha Alicia , Lopez-Montero, Luis Miguel

In this work, a new medical image encryption/decryption algorithm was proposed. It is based on three main parts: the Jigsaw transform, Langton’s ant, and a novel way to add deterministic noise. The Jigsaw transform was used to hide visual information effectively, whereas Langton’s ant and the deterministic noise algorithm give a reliable and secure approach. As a case study, the proposal was applied to high-resolution retinal fundus images, where a zero mean square error was obtained between the original and decrypted image. The method performance has been proven through several testing methods, such as statistical analysis (histograms and correlation distributions), entropy computation, keyspace assessment, robustness to differential attack, and key sensitivity analysis, showing in each one a high security level. In addition, the method was compared against other works showing a competitive performance and highlighting with a large keyspace (>1×101,134,190.38). Besides, the method has demonstrated adequate handling of high-resolution images, obtaining entropy values between 7.999988 and 7.999989, an average Number of Pixel Change Rate (NPCR) of 99.5796%±0.000674, and a mean Uniform Average Change Intensity (UACI) of 33.4469%±0.00229. In addition, when there is a small change in the key, the method does not give additional information to decrypt the image. ©2021 Axioms, MDPI.

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A Computer Vision Approach to Terminus Movement Analysis of Viedma Glacier

2023 , Moya-Albor, Ernesto , Schwartzman, Armin , Brieva, Jorge , Pardo, Mauricio , Ponce, Hiram , Chávez-Domínguez, Rodrigo

In this paper, an automatic segmentation approach of the Viedma glacier terminus is proposed. The method uses multi-spectral images from the Landsat-5 satellite to determine the area of the glacier through computer vision techniques. The area of the glacier is estimated, and a linear model is fitted, obtaining a correlation of 0.968 between the measured area and a fit linear regression model. On the other hand, a bio-inspired optical flow estimation approach is used to calculate and visualize the displacement of the glacier through time. In addition, an analysis is performed between the temperature variation in the Southern Cone and the decrease of the glacier in the function of time. A linear trend (r2=0.95) shows that the analyzed area of the glacier has decreased by about 1.9% annually in the observation season. It reveals an inverse relationship between the change in the size of the glacier and global warming, showing that if the same conditions remain, the glacier's zone analyzed in this work would be close to its disappearance in around 70 years, the time lapse in which a global temperature increase of 1.24 oC would be reached. © 2023 IEEE.

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Motion magnification using the Hermite transform

2015 , Brieva, Jorge , Gomez-Coronel, Sandra L. , Moya-Albor, Ernesto , Escalante-Ramírez, Boris , Mora Esquivel, Juan I. , Ponce, Hiram

We present an Eulerian motion magnification technique with a spatial decomposition based on the Hermite Transform (HT). We compare our results to the approach presented in. We test our method in one sequence of the breathing of a newborn baby and on an MRI left ventricle sequence. Methods are compared using quantitative and qualitative metrics after the application of the motion magnification algorithm.

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Distance Estimation Using a Bio-Inspired Optical Flow Strategy Applied to Neuro-Robotics

2018 , Ponce, Hiram , Brieva, Jorge , Moya-Albor, Ernesto

Movement detection and characterization of a 3D scene are relevant tasks in vision systems and particularly in robotic applications controlled by visual features. One of the challenges to characterize a 3D scene in navigation systems is the depth estimation. In contrast to classical approaches using visual based stereo systems, we propose a monocular distance estimation system using convolutional neural networks (CNN) and a bio-inspired optical flow approach as part of a neuro-robotic system. We train the CNN using optical flow visual features guided by ultrasonic sensor-based measures in a 3D scenario. The datasets used are available in: http://sites.google.com/up.edu.mx/robotflow/. Experimental results confirm that a monocular camera can be applie for controlling the robot navigation and obstacle avoidance.

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A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset

2019 , Espinosa Loera, Ricardo Abel , Ponce, Hiram , Moya-Albor, Ernesto , Martinez-Villaseñor, Lourdes , Brieva, Jorge , Gutiérrez, Sebastián

The automatic recognition of human falls is currently an important topic of research for the computer vision and artificial intelligence communities. In image analysis, it is common to use a vision-based approach for fall detection and classification systems due to the recent exponential increase in the use of cameras. Moreover, deep learning techniques have revolutionized vision-based approaches. These techniques are considered robust and reliable solutions for detection and classification problems, mostly using convolutional neural networks (CNNs). Recently, our research group released a public multimodal dataset for fall detection called the UP-Fall Detection dataset, and studies on modality approaches for fall detection and classification are required. Focusing only on a vision-based approach, in this paper, we present a fall detection system based on a 2D CNN inference method and multiple cameras. This approach analyzes images in fixed time windows and extracts features using an optical flow method that obtains information on the relative motion between two consecutive images. We tested this approach on our public dataset, and the results showed that our proposed multi-vision-based approach detects human falls and achieves an accuracy of 95.64% compared to state-of-the-art methods with a simple CNN network architecture. © 2019 Elsevier Ltd

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Thoughts and emotion assimilation and detonation through VR for people with ASD

2018 , Moya-Albor, Ernesto , Hernández Mosti, Juan P. , Cañete Alavez, Mariela , Vaillard Martínez, Judith , Reza Becerril, Diego , Brieva, Jorge

This study proposes a new tool based on Virtual Reality (VR) as a complement in the treatment of people diagnosed with Autism Spectrum Disorder (ASD). VR tools have been stablished in last years as a new option in learning and practising new skills during the treatment. In this work, a VR application is developed simulating several environments corresponding to di€erent types of emotions according to the Gestalt school of psychology. The VR application was tested in five male teenagers diagnosed with ASD of level one according to the DSM-5 during the therapy sessions. A qualitative evaluation of the VR application is carried out by the therapist during the session. It is observed and annotated which emotions have been detonated by the VR application giving to the therapist new information for the subsequent sessions. © SPIE. Downloading of the abstract is permitted for personal use only.

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