
Luiz Marcos G. GonçalvesFederal University of Rio Grande do Norte | IIP · Department of Computer Engineering and Automation
Luiz Marcos G. Gonçalves
Ph.D. Robotics Vision
Prof. Electrical and Computer Engineering Graduate Program, and head of Natalnet Associate Labs, UFRN, Brazil.
About
278
Publications
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Introduction
Luiz Goncalves holds a Doctorate in Robotics Vision from Laboratory for Computer Graphics and Vision at the Systems and Computer Engineering Dept of COPPE-UFRJ, Brazil, in 1999, with a 2 years sandwich at Laboratory for Perceptual Robotics of UMASS, Amherst, MA, USA. He is Full Professor at the Computer Engineering Department of UFRN, Brazil. He has done researches in the several aspects of Graphics Processing including fields as Robotics Vision (main interest), Computer Graphics, GIS, Geometric Modeling, Computer Animation, Image Processing, Computer Vision, and on Robotics in Education.
Additional affiliations
Education
July 1995 - July 1999
Publications
Publications (278)
Devido ao crescente desenvolvimento tecnológico da sociedade contemporânea, a robótica educacional tem crescido como uma ferramenta que vem auxiliando vários estudantes, professores e entusiastas da área, a estudarem e desenvolverem projetos para solucionar problemas, dentre eles os presentes no mundo atual. Existem hoje diversos kits de robótica e...
The SARS-CoV-2 global pandemic prompted governments, institutions, and researchers to investigate its impact, developing strategies based on general indicators to make the most precise predictions possible. Approaches based on epidemiological models were used but the outcomes demonstrated forecasting with uncertainty due to insufficient or missing...
Visual odometry (VO) is an important problem studied in robotics and computer vision in which the relative camera motion is computed through visual information. In this work, we propose to reduce the error accumulation of a dual stereo VO system (4 cameras) computing 6 degrees of freedom poses by fusing two independent stereo odometry with a nonlin...
EREMITE is a low-cost and open multi-sensory system that monitors and digitises our coastal marine ecosystems to understand their state, ecological health and functioning, with the concept of any sensor, anytime, anywhere. It is made of an optical multi-sensing system onboard an autonomous sailboat that perceives and reasons about underwater abioti...
The epidemiology of COVID-19 presented major shifts during the pandemic period. Factors such as the most common symptoms and severity of infection, the circulation of different variants, the preparedness of health services, and control efforts based on pharmaceutical and non-pharmaceutical interventions played important roles in the disease inciden...
Unmanned vehicles keep growing attention as they facilitate innovative commercial and civil applications within the Internet of Things (IoT) realm. In this context, autonomous sailing boats are becoming important marine platforms for performing different tasks, such as surveillance, water, and environmental monitoring. Most of these tasks heavily d...
In this article, we perform the SARIMA model to regress the curve of daily COVID-19 deaths and the impact of implementing restrictive measures like lockdown. For comparison, we adopt two neighboring Brazilian cities with similar characteristics and decompose the original curve of cases to extract the seasonal curve. Using Fast Fourier Transform, we...
We propose a platform consisting of a data lake that has been implemented as a web-based service, to specifically solve the Covid-19 data production and processing problem. The main idea is that it can be used by data scientists working on COVID-19-related projects in order to access as much data as possible in one repository and be able not only t...
This work is the result of the joint efforts of professionals encouraged to build a solution to predict the contagion and death curves of the Covid-19 pandemic, through the use of data-oriented solutions. This strategy is fundamentally dependent on collection. Regarding this particular aspect, the difficulty is manifested due to the fact that such...
One of the topics that have been recently discussed with greater emphasis is air quality, not only because it is a topic directly related to climate change and the greenhouse effect, but also because it has a strong link in the transmission of respiratory diseases. Low-quality indices of air can worsen the symptoms of patients with the COVID-19 pan...
The Behavioral Neurophysiology research area investigates the electrophysiological correlates of behaviors, normally using animals such as rodents as subjects. Examples of studies in the field include the investigation of neural processing dysfunctions and synaptic plasticity in animal models of autism and changes in synaptic plasticity in animal m...
Due to the global pandemic disclaimer caused by the SARS-COV-2 virus propagation, also called COVID-19, governments, institutions, and researchers have mobilized intending to try to mitigate the effects caused by the virus on society. Some approaches were proposed and applied to try to make predictions of the behavior of possible pandemics indicato...
This work presents the development, calibration, and validation of a device capable of actively capturing data related to the measurement of air quality for future prevention. This data can then be compared with pandemic/endemic data indices by location using PM2.5, temperature, and humidity sensors, along with a microcontroller capable of sending...
We draw current efforts towards proposing a wing-type micro UAV with characteristics of being a basic operation risk self handled (Micro-Brosh) platform. Its micro-sized wingspan and weight, which are less than 0.30 m and 0.150 kg, respectively, guarantee the low risk to the operator and installations in case of crashing. It can be launched manuall...
Strategic management and production of internal energy in autonomous robots is becoming a research topic with growing importance, especially for platforms that target long-endurance missions, with long-range and duration. It is fundamental for autonomous vehicles to have energy self-generation capability to improve energy autonomy, especially in si...
There are important questions surrounding the potential contribution of outdoor and indoor air quality in the transmission of SARS-CoV-2 and perpetuation of COVID-19 epidemic waves. Environmental health may be a critical component of COVID-19 prevention. The public health community and health agencies should consider the evolving evidence in their...
This chapter introduces a thorough discussion about the current tools to estimate the epidemiology of COVID-19 focusing on AI strategies. We present in detail both the traditional methods for pandemics forecasting, namely, the SIR, SEIR, SEIRS, SIRD, and ARIMA and novel data-driven approaches that presented promising results, the LSTM, AE, MAE, CNN...
We propose a new double-hybrid concept and architectural design of a tailsitter unmanned aerial vehicle with vertical takeoff and landing capability. Basically, it consists of a modified flying wing with a single combustion powertrain set and a multirotor with 2 powertrain sets with electric motors. With the electric propellers fixed at the leading...
This work presents the development, test, and validation of a system that gathers and analyses data from optical sensors to monitor the air quality of indoor environments to help prevent Severe Acute Respiratory Syndromes (SARS).
In this paper, we investigate the influence of holidays and community mobility on the transmission rate and death count of COVID-19 in Brazil. We identify national holidays and hallmark holidays to assess their effect on disease reports of confirmed cases and deaths. First, we use a one-variate model with the number of infected people as input data...
Since the start of the COVID-19 pandemic many studies investigated the correlation between climate variables such as air quality, humidity and temperature and the lethality of COVID-19 around the world. In this work we investigate the use of climate variables, as additional features to train a data-driven multivariate forecast model to predict the...
Target detection enables running a robotic task. However, their limited resources make large amount of data processing harder. Image foveation is an approach that can reduce processing demand by reducing the amount of data to be processed. However, as an important visual stimulli can be attenuated by this reduction, some strategy should be applied...
Target detection enables running a robotic task. However, their limited resources make large amount of data processing harder. Image foveation is an approach that can reduce processing demand by reducing the amount of data to be processed. However, as an important visual stimulli can be attenuated by this reduction, some strategy should be applied...
With advances in science and technology, several innovative researches have been developed trying to figure out the main problems related to children’s learning. It is known that issues such as frustration and inattention, between others, affect student learning. In this fashion, robotics is an important resource that can be used towards helping to...
This paper proposes a learning framework for Educational Robotics named sBotics, which includes a complete environment for teaching and programming skills acquisition designed for both teachers and K-12 students. Our framework has been developed using a gamified approach with the system and simulated environment developed in the Unity game engine....
The adverse effects of fine particulate matter and many volatile organic substances on human health are well known. Fine particles are, in fact, those most capable of penetrating in depth into the respiratory system. People spend most of their time indoors where concentrations of some pollutants are sometimes higher than outdoors. Therefore, there...
Artificial marker mapping is a useful tool for fast camera localization estimation with a certain degree of accuracy in large indoor and outdoor environments. Nonetheless, the level of accuracy can still be enhanced to allow the creation of applications such as the new Visual Odometry and SLAM datasets, low-cost systems for robot detection and trac...
We propose a way to perform the classification of holographic phase maps using machine learning models in a web application. The system can perform acquisition, processing, reconstruction, segmentation, and classification steps straight from the browser.
Among the studies done with rodents, the behavioral ones stand out. To perform these studies, the behavioral boxes are commonly used. These are devices in which the rodents perform some task to receive a reward. These animals are considered excellent subjects for studying the tactile sensory system, since they use their whiskers to locate and discr...
This article proposes the BIPES, a
B
lock based
I
ntegrated
P
latform for
E
mbedded
S
ystems, including its architecture, design and validation results. BIPES is an open source software and service that is freely available through the website
http://www.bipes.net.br
and has been conceived from our experience of several years developing...
Diatoms are among the dominant phytoplankters in marine and freshwater habitats, and important biomarkers of water quality, making their identification and classification one of the current challenges for environmental monitoring. To date, taxonomy of the species populating a water column is still conducted by marine biologists on the basis of thei...
Foveation is a technique that allows real-time image processing by drastically reducing the amount of visual data without loosing essential information around some focused area. When a robot needs to pay attention at two or more regions of the image at the same time, e.g., for tracking two or more objects, multifoveation is necessary. In this case,...
Object Detection (OD) is an important task in Computer Vision with many practical applications. For some use cases, OD must be done on videos, where the object of interest has a periodic motion. In this paper, we formalize the problem of periodic OD, which consists in improving the performance of an OD model in the specific case where the object of...
Noise coming from sensors or caused by external world phenomena results in measurement errors that cause uncertainties in some robotic tasks, e.g. tracking a robot displacement and tracking an observed target. Control approaches such as model predictive control (MPC) usually guarantee constraints satisfaction by way of using detailed models of pred...
The contribution of this paper is twofold. First, a new data driven approach for predicting the Covid-19 pandemic dynamics is introduced. The second contribution consists in reporting and discussing the results that were obtained with this approach for the Brazilian states, with predictions starting as of 4 May 2020. As a preliminary study, we firs...
This paper has a twofold contribution. The first is a data driven approach for predicting the Covid-19 pandemic dynamics, based on data from more advanced countries. The second is to report and discuss the results obtained with this approach for Brazilian states, as of May 4th, 2020. We start by presenting preliminary results obtained by training a...
A atividade do profissional da área de informática exige longas horas seguidas em uma mesma posição (sentada), que geralmente é estabelecida de maneira inadequada, causando vícios de posturas. Existem recomendações e exercícios para evitar esses vícios e até mesmo a fisioterapia para tentar sanar os danos causados. O presente trabalho realiza um es...
Background
Epidemiological figures of Covid-19 epidemic in Italy are worse than those observed in China.
Methods
We modeled the Covid-19 outbreak in Italian Regions vs. Lombardy to assess the epidemics progression and predict peaks of new daily infections and total cases by learning from the entire Chinese epidemiological dynamics. We trained an a...
Path planning for sailboat robots is a challenging task particularly due to the kinematics and dynamics modelling of such kinds of wind propelled boats. The problem is divided into two layers. The first one is global were a general trajectory composed of waypoints is planned, which can be done automatically based on some variables such as weather c...
Audio description (AD) is an assistive technology that allows visually impaired people to access cinema and understand the story of a movie. Basically, the visual content of the story is told by way of using a voice, narrated during the film gaps of silence. Nonetheless, this assistive technology is not widely used, due to several factors, among th...
It is well known that relational databases still play an important role for many companies around the world. For this reason, the use of data mining methods to discover knowledge in large relational databases has become an interesting research issue. In the context of unsupervised data mining, for instance, the conventional clustering algorithms ca...
We present and test a prototype of a compact, light in weight, cost effective and field portable off-axis DH microscope based on the concept of the Holographic Microscope Slide.
In this manuscript, we propose an approach that allows a team of robots to create new (emergent) behaviors at execution time. Basically, we improve the approach called N-Learning used for self-programming of robots in a team, by modifying and extending its functioning structure. The basic capability of behavior sharing is increased by the catching...
Since it was proposed, the Robot Operating System (ROS) has fostered solutions for various problems in robotics in the form of ROS packages. One of these problems is Simultaneous Localization and Mapping (SLAM), a problem solved by computing the robot pose and a map of its environment of operation at the same time. The increasingly availability of...