Urbano J. Nunes

• PhD
• Professor at University of Coimbra

Planar 3D reconstruction presents advantages over point cloud representations. This work focuses on the acceleration of piecewise-planar-based 3D reconstruction, a StereoScan method. We identify the SymStereo (logN) and uncapacitated facility location (UFL) algorithms as the most computationally expensive tasks, consuming nearly 80 × of total runti...

Brain-controlled wheelchairs (BCWs) are a promising solution for severely motor-disabled people who cannot use conventional interfaces. Compared to other brain-computer interfaces (BCIs), e.g., spellers and games, BCWs are more complex, combining BCI and assistive navigation systems (ANS), and require higher levels of reliability and usability to e...

The regeneration factor, that expresses the ratio between the energy recovered to the battery during braking and the total braking energy, is difficult to be measured from independent instruments. In this paper, a reinforcement learning (RL) method is used to adjust and improve a fuzzy logic model for regenerative braking (FLmRB) for modeling Elect...

This work proposes a robot-assisted navigation approach based on user intent adjustment, in the context of robotic walkers. Walkers are prescribed to users with gait disorders so that they can support their body weight on the upper limbs, however, the manipulation of such devices can be cumbersome for some users. Common problems for the users are l...

In this paper we present an improvement of the ISR-RobotHead prototype interaction capabilities having in view future Human-Robot Interactions studies. To accomplish that, a new hardware and software architectures and new facial expressions were developed. This new prototype (ISR-RobotHead v2.0) uses LCDs to display six human facial emotional expre...

An Electrooculography-based method is used to correct misclassification of P300 event related potentials in a Lateral Character Speller (LSC) Brain-Computer Interface (BCI). The LSC speller’s circular layout allows us to combine P300 detection with the detection of eye movements to improve symbol detection reliability. We separately classify the ve...

In this paper we present an improvement of the ISR-RobotHead prototype interaction capabilities having in view future Human-Robot Interactions studies. To accomplish that, a new hardware and software architectures and new facial expressions were developed. This new prototype (ISR-RobotHead v2.0) uses LCDs to display six human facial emotional expre...

Traditional dense stereo estimation algorithms measure photo-similarity to calculate the disparity between image pairs. SymStereo is a new framework of matching cost functions that measure symmetry to evaluate the possibility of two pixels being a match. This article proposes a fully functional real-time parallel 3D reconstruction pipeline that use...

This paper analyzes the galvanic skin response (GSR) recorded from healthy and motor disabled people while steering a robotic wheelchair (RobChair ISR-UC prototype), to infer whether GSR can help in the recognition of stressful situations. Seven healthy individuals and six individuals with motor disabilities were asked to drive the RobChair by mean...

This article presents a novel intersection traffic management system for automated vehicles and quantifies its impact on fuel consumption and greenhouse gas emissions of CO2 relative to traditional traffic signal and roundabout intersection control. The developed intelligent traffic management (ITM) techniques, which are based on a spatiotemporal r...

This paper presents a study on pedestrian classification based on deep learning using data from a monocular camera and a 3D LIDAR sensor, separately and in combination. Early and late multi-modal sensor fusion approaches are revisited and compared in terms of classification performance. The problem of pedestrian classification finds applications in...

Model-based positioning methods involve nonlinear equations as is the case when using satellite pseudoranges on global navigation satellite systems (GNSSs) and local measurements on road features. As these are nonlinear models, classical estimation methods cannot provide guaranteed position estimation and can converge to local optima, sometimes far...

This paper addresses the problem of vehicle detection using a little explored LIDAR’s modality: the reflection intensity. LIDAR reflection measures the ratio of the received beam sent to a surface, which depends upon the distance, material, and the angle between surface normal and the ray. Considering a 3D-LIDAR mounted on board a robotic vehicle,...

Brain-computer interface (BCI) is a useful device for people with severe motor disabilities. However due to its low speed and low reliability, BCI still has a very limited application in daily real-world tasks. This paper proposes a P300-based BCI speller combined with a double error-related potential (ErrP) detection to automatically correct erron...

Most of the current successful object detection approaches are based on a class of deep learning models called Convolutional Neural Networks (ConvNets). While most existing object detection researches are focused on using ConvNets with color image data, emerging fields of application such as Autonomous Vehicles (AVs) which integrates a diverse set...

This paper addresses the problem of vehicle detection using Deep Convolutional Neural Network (ConvNet) and 3D-LIDAR data with application in advanced driver assistance systems and autonomous driving. A vehicle detection system based on the Hypothesis Generation (HG) and Verification (HV) paradigms is proposed. The data inputted to the system is a...

This paper addresses the problem of vehicle detection using a little explored LIDAR's modality: the reflection intensity. LIDAR reflection measures the ratio of the received beam sent to a surface, which depends upon the distance, material, and the angle between surface normal and the ray. Considering a 3D-LIDAR mounted on board a robotic vehicle,...

In this paper, the problem of semantic place cate-gorization in mobile robotics is addressed by considering a time-based probabilistic approach called Dynamic Bayesian Mixture Model (DBMM), which is an improved variation of the Dynamic Bayesian Network (DBN). More specifically , multi-class semantic classification is performed by a DBMM composed of...

Cooperation between road users through V2X communication is a way to improve GNSS localization accuracy. When vehicles localization systems involve standalone GNSS receivers, the resulting accuracy can be affected by satellite-specific errors of several meters. This paper studies how road-features like lane marking detected by on-board cameras can...

Objective. The achievement of multiple instances of control with the same type of mental strategy represents a way to improve flexibility of brain–computer interface (BCI) systems. Here we test the hypothesis that pure visual motion imagery of an external actuator can be used as a tool to achieve three classes of electroencephalographic (EEG) based...

The articles in this special section examine safety and security concerns with intelligent vehicle technologies. The most demanding and challenging quality attribute the manufacturers of aerial and ground vehicles must guarantee is safety, meaning that its usage is, to a reasonable level, free from failures with catastrophic consequences on the use...

Several applications in robotics require complex sensor arrangements that must be carefully calibrated, both intrinsically and extrinsically, to allow information fusion and enable the system to function as a whole. These arrangements can combine different sensing modalities—such as color cameras, laser-rangefinders, and depth cameras—in an attempt...

With its acquisition of muscular potentials linked to displays of affective state, facial Electromyography (EMG) is the most fitting physiological signal for performing emotional expressions detection. EMG and computer vision-based facial recognition have very different strengths and weaknesses, but their information may complement each other. Addi...

Worldwide, several research works have been devoted to the development of humanoid robots for human-robot interaction (HRI). Particular attention has been paid to the concept, design and applications of robotic heads and facial-expressions. Together, head and its facial expressions, they compose a fundamental, and “familiar”, interface to end-users...

This article presents a new hybrid motion (HM) planner, designed to allow robust indoor navigation in constrained environments of nonholonomic differential robots, such as RobChair, the brain-actuated robotic wheelchair [1] from the Institute of Systems and Robotics, University of Coimbra, Portugal. Relying on this new planning algorithm, RobChair...

Object tracking is one of the key components of the perception system of autonomous cars and ADASs. With tracking, an ego-vehicle can make a prediction about the location of surrounding objects in the next time epoch and plan for next actions. Object tracking algorithms typically rely on sensory data (from RGB cameras or LIDAR). In fact, the integr...

Research in autonomous driving has matured significantly with major automotive companies making important efforts to have their autonomous or highly automated cars available in the near future. As driverless cars move from laboratories to complex real-world environments, the perception capabilities of these systems to acquire, model and interpret t...

High resolution depth-maps, obtained by upsampling sparse range data from a 3D-LIDAR, find applications in many fields ranging from sensory perception to semantic segmentation and object detection. Upsampling is often based on combining data from a monocular camera to compensate the low-resolution of a LIDAR. This paper, on the other hand, introduc...

In this work, we present a real-time application in the scope of human daily activity recognition for robot-assisted living as an extension of our previous work [1]. We implemented our approach using Robot Operating System (ROS) environment, combining different modules to enable a robot to perceive the environment using different sensor modalities....

Social activity based on body motion is a key feature for non-verbal and physical behavior defined as function for communicative signal and social interaction between individuals. Social activity recognition is important to study human-human communication and also human-robot interaction. Based on that, this research has threefold goals: (1) recogn...

In real-world applications the assumption of independent and identical distribution (i.i.d.) is no longer consistent. To alleviate the significant mismatch between source and target domains, importance weighting import vector machine (IWIVM), which is an adaptive classifier, is proposed. This adaptive probabilistic classification method, which is s...

Human body motion analysis is an initial procedure for understanding and perceiving human activities. A multilevel approach is proposed here for automatic human activity and social role identification. Different topics contribute to the development of the proposed approach, such as feature extraction, body motion description and probabilistic model...

In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called Dynamic Bayesian Mixture Model (DBMM), which is an improved variation of the Dynamic Bayesian Network (DBN). More specifically, multi-class semantic classification is performed by a DBMM composed of a...

High resolution depth-maps, obtained by upsampling sparse range data from a 3D-LIDAR, find applications in many fields ranging from sensory perception to semantic segmentation and object detection. Upsampling is often based on combining data from a monocular camera to compensate the low-resolution of a LIDAR. This paper, on the other hand, introduc...

Artificial perception, in the context of autonomous driving, is the process by which an intelligent system translates sensory data into an effective model of the environment surrounding a vehicle. In this paper, and considering data from a 3D-LIDAR mounted onboard an intelligent vehicle, a 3D perception system based on voxels and planes is proposed...

A major challenge in brain-computer interface (BCI) research is to increase the number of command classes and levels of control. BCI studies often use binary control level approaches (level 0 and 1 of brain activation for each class of control). Different classes may often be achieved but not different levels of activation for the same class. The i...

Summary of whole-brain regions activated during visual motion imagery. Peak voxels according Talairach coordinates and the number of used voxels (FFX, q(FDR) = 0.05 using the contrast up-regulation tasks versus down-regulation task. Results presented per imagery run: passive imagery run (control run without feedback), imagery runs with feedback (ne...

The article describes a reconstruction pipeline that generates piecewise-planar models of man-made environments using two calibrated views. The 3D space is sampled by a set of virtual cut planes that intersect the baseline of the stereo rig and implicitly define possible pixel correspondences across views. The likelihood of these correspondences be...

Perception is the process by which an intelligent system translates sensory data into an understanding of the world around it. Perception of dynamic environments is one of the key components for intelligent vehicles to operate in real-world environments. This paper proposes a method for static/dynamic modeling of the environment surrounding a vehic...

In this work, we present a real-time application in the scope of human daily activity recognition for robot-assisted living as an extension of our previous work [1]. We implemented our approach using Robot Operating System (ROS) environment, combining different modules to enable a robot to perceive the environment using different sensor modalities....

Understanding human behavior through nonverbal-based features, is interesting in several applications such as surveillance, ambient assisted living and human-robot interaction. In this article in order to analyze human behaviors in social context, we propose a new approach which explores interrelations between body part motions in scenarios with pe...

To facilitate the performance comparison of new methods for sleep patterns analysis, datasets with quality content, publicly-available, are very important and useful. We introduce an open-access comprehensive sleep dataset, called ISRUC-Sleep. The data were obtained from human adults, including healthy subjects, subjects with sleep disorders, and s...

Perception is the process by which an intelligent system translates sensory data into an understanding of the world around it. 3D perception of dynamic environments is one of the key components for intelligent vehicles to operate in real-world environments. This paper proposes a voxel-based method for static/dynamic modeling of the three-dimensiona...

Autonomous vehicles require a reliable perception of their environment to operate in real-world conditions. Awareness of moving objects is one of the key components for the perception of the environment. This paper proposes a method for detection and tracking of moving objects (DATMO) in dynamic environments surrounding a moving road vehicle equipp...

Resumo—This paper presents a collaborative self-localization approach using a multi-GNSS receiver setup and V2V/V2I communications. The purpose is to develop a low-cost alternative (equipment and installation), without compromising the process of localiza-tion estimation. The proposed method uses two GPS-receivers installed on the vehicle, disposed...

In this paper a spatial interpolation approach, based on polar-grid representation and Kriging predictor, is proposed for 3D point cloud sampling. Discrete grid representation is a widely used technique because of its simplicity and capacity of providing an efficient and compact representation, allowing subsequent applications such as artificial pe...

In this work, we present a human-centered robot application in the scope of daily activity recognition towards robot-assisted living. Our approach consists of a probabilistic ensemble of classifiers as a dynamic mixture model considering the Bayesian probability, where each base classifier contributes to the inference in proportion to its posterior...

This paper presents a fuzzy logic model of regenerative braking (FLmRB) for modeling EVs’ regenerative braking systems (RBSs). The model has the vehicle’s acceleration and jerk, and the road inclination as input variables, and the output of the FLmRB is the regeneration factor, i.e. the ratio of regenerative braking force to the total braking force...

The four articles in this special section focus on planning and development of autonomous vehicles. These contributions discuss important aspects that mark trends in autonomous driving as well as complete system architectures of successful implementations. Foremost, maps have enabled autonomous driving over long distances and it comes hardly as a s...

This research characterizes mobility, accessibility and safety of individuals with severe motor impairment such as users suffering from Cerebral Palsy (CP). Through the analysis of enabling factors, constraints associated and the search of possible improvements, it is possible to identify the needs in these fields and subsequently develop strategie...

The ability of an intelligent system to recognize the user's emotional and mental states is of considerable interest for human-robot interaction and human-machine interfaces. T his paper describes an automatic recognizer of the facial expression around the eyes and forehead based on electrooculographic (EOG) signals. Six movements of the eyes, name...

This paper proposes a road detection approach based solely on dense 3D-LIDAR data. The approach is built up of four stages: (1) 3D-LIDAR points are projected to a 2D reference plane; then, (2) dense height maps are computed using an upsampling method; (3) applying a sliding-window technique in the upsampled maps, probability distributions of neighb...

Electric vehicle (EV) powertrain dynamics and steady state parameters can only be acquired in controlled test conditions, what is not possible to obtain experimentally in real road traffic. This paper presents a test bench designed for modelling purposes of small EVs such as ISRobotCar [2]. The EV powertrain was tested to acquire the motor power dr...

Multiplatooning leaders positioning and cooperative behavior strategies are proposed in this paper, to improve the efficiency of a traffic system of communicant automated vehicles evolving on dedicated lanes. Novel algorithms to ensure high traffic capacity are presented and MATLAB/Simulink-based simulation results are reported. In previous researc...

Why is pedestrian detection still very challenging in realistic scenes? How much would a successful solution to monocular depth inference aid pedestrian detection? In order to answer these questions we trained a state-of-the-art deformable parts detector using different configurations of optical images and their associated 3D point clouds, in conju...

In this work, we propose an approach that relies on cues from depth perception from RGB-D images, where features related to human body motion (3D skeleton features) are used on multiple learning classifiers in order to recognize human activities on a benchmark dataset. A Dynamic Bayesian Mixture Model (DBMM) is designed to combine multiple classifi...

Advances in autonomous navigation, safety, and natural-landmark based localization, are among the key objectives in the development of the next generation of autonomous vehicles, to be deployed in manufacturing and semi-structured environments. In this paper, autonomous navigation and collision detection will be focused, where it is proposed a nove...

The conventional iris recognition methods do not perform well for the datasets where the eye image may contain nonideal data such as specular reflection, off-angle view, eyelid, eyelashes and other artifacts. This paper gives contributions for a reliable iris recognition method using a new scale-, shift- and rotationinvariant feature-extraction met...

SymStereo is a new algorithm used for stereo estimation. Instead of measuring photo-similarity, it proposes novel cost functions that measure symmetry for evaluating the likelihood of two pixels being a match. In this work we propose a parallel approach of the LogN matching cost variant of SymStereo capable of processing pairs of images in real-tim...

This work presents a method for simultaneous segmentation and modeling of objects, detected in range data gathered by a laserscanner mounted on-board ground-robotic platforms. Superquadrics are used as model for both segmentation and object shape fitting. The proposed method, which we name Simultaneous Segmentation and Superquadrics Fitting (S3F),...

The cascade classifier is a usual approach in object detection based on vision, since it successively rejects negative occurrences, e.g., background images, in a cascade structure, keeping the processing time suitable for on-the-fly applications. On the other hand, similar to other classifier ensembles, cascade classifiers are likely to have high V...

To improve applicability of automatic sleep staging an efficient subject-independent method is proposed with application in sleep-wake detection and in multiclass sleep staging (awake, non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep). In turn, NREM is further divided into three stages denoted here by N1, N2, and N3. To assess...

This paper describes a legacy algorithm for an intelligent traffic management system applied to automatic regulation of traffic at intersections. The application of the legacy algorithm enables the intelligent intersection to accommodate vehicles, in a low percentage, not equipped or with faulty V2V and V2I communications. The developed intelligent...

This paper presents an experimental study on pedestrian classification and detection in far infrared (FIR) images. The study includes an in-depth evaluation of several combinations of features and classifiers, which include features previously used for daylight scenarios, as well as a new descriptor (HOPE – Histograms of Oriented Phase Energy), spe...

Road segmentation plays an important role in many computer vision applications, either for in-vehicle perception or traffic surveillance. In camera-equipped vehicles, road detection methods are being developed for advanced driver assistance, lane departure, and aerial incident detection, just to cite a few. In traffic surveillance, segmenting road...

The article describes a new algorithm for calibrating a Kinect sensor that achieves high accuracy using only 6 to 10 image-disparity pairs of a planar checkerboard pattern. The method estimates the projection parameters for both color and depth cameras, the relative pose between them, and the function that converts kinect disparity units (kdu) into...

The most standard image object detectors are usually comprised of one or multiple feature extractors or classifiers within a sliding window framework. Nevertheless, this type of approach has demonstrated a very limited performance under datasets of cluttered scenes and real life situations. To tackle these issues, LIDAR space is exploited here in o...

This paper presents a brain-computer interface game that controls a spacecraft that has to avoid obstacles in a space route. The neural mechanism is based on steady state visually evoked potentials (SSVEP) combined with phase tagging. Two flickering stimuli are used to move the spacecraft to left or right. The stimuli are tagged with a phase offset...