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About

About

Hi!

I'm a senior researcher at Centre for Robotics and Autonomous Systems (CRAS) at INESC TEC.

I have received a MS.c. degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto (FEUP) in 2005, and a Ph.D. from the Department of Electrical and Computer Engineering of FEUP, Portugal, in 2014.

I'm being involved in several R&D projects for the last 7 years (related with mobile robotic, intelligent systems and autonomous platforms) as well as in some partnerhips with the industry. Moreover, I'm the principal author of several articles in top-ranked journals of robotics and computer vision.

Currently, my research interests include artificial intelligence, robotics, visual motion perception, motion analysis, optical flow, unsupervised segmentation, 3D reconstructions and underwater imaging.

Interest
Topics
Details

Details

006
Publications

2019

A mosaicking technique for object identification in underwater environments

Authors
Nunes, AP; Silva Gaspar, ARS; Pinto, AM; Matos, AC;

Publication
Sensor Review

Abstract
Purpose: This paper aims to present a mosaicking method for underwater robotic applications, whose result can be provided to other perceptual systems for scene understanding such as real-time object recognition. Design/methodology/approach: This method is called robust and large-scale mosaicking (ROLAMOS) and presents an efficient frame-to-frame motion estimation with outlier removal and consistency checking that maps large visual areas in high resolution. The visual mosaic of the sea-floor is created on-the-fly by a robust registration procedure that composes monocular observations and manages the computational resources. Moreover, the registration process of ROLAMOS aligns the observation to the existing mosaic. Findings: A comprehensive set of experiments compares the performance of ROLAMOS to other similar approaches, using both data sets (publicly available) and live data obtained by a ROV operating in real scenes. The results demonstrate that ROLAMOS is adequate for mapping of sea-floor scenarios as it provides accurate information from the seabed, which is of extreme importance for autonomous robots surveying the environment that does not rely on specialized computers. Originality/value: The ROLAMOS is suitable for robotic applications that require an online, robust and effective technique to reconstruct the underwater environment from only visual information. © 2018, Emerald Publishing Limited.

2019

An Hierarchical Architecture for Docking Autonomous Surface Vehicles

Authors
Leite, P; Silva, R; Matos, A; Pinto, AM;

Publication
2019 19TH IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2019)

Abstract
Autonomous Surface Vehicles (ASVs) provide the ideal platform to further explore the many opportunities in the cargo shipping industry, by making it more profitable and safer. This paper presents an architecture for the autonomous docking operation, formed by two stages: a maneuver module and, a situational awareness system to detect a mooring facility where an ASV can safely dock. Information retrieved from a 3D LIDAR, IMU and GPS are combined to extract the geometric features of the floating platform and to estimate the relative positioning and orientation of the moor to the ASV. Then, the maneuver module plans a trajectory to a specific position and guarantees that the ASV will not collide with the mooring facility. The approach presented in this paper was validated in distinct environmental and weather conditions such as tidal waves and wind. The results demonstrate the ability of the proposed architecture for detecting the docking platform and safely conduct the navigation towards it, achieving errors up to 0.107 m in position and 6.58 degrees in orientation.

2019

Hybrid Approach to Estimate a Collision-Free Velocity for Autonomous Surface Vehicles

Authors
Silva, R; Leite, P; Campos, D; Pinto, AM;

Publication
2019 19TH IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2019)

Abstract
Shipping transportation mode needs to be even more efficient, profitable and secure as more than 80% of the world's trade is done by sea. Autonomous ships will provide the possibility to eliminate the likelihood of human error, reduce unnecessary crew costs and increase the efficiency of the cargo spaces. Although a significant work is being made, and new algorithms are arising, they are still a mirage and still have some problems regarding safety, autonomy and reliability. This paper proposes an online obstacle avoidance algorithm for Autonomous Surfaces Vehicles (ASVs) introducing the reachability with the protective zone concepts. This method estimates a collision-free velocity based on inner and outer constraints such as, current velocity, direction, maximum speed and turning radius of the vehicle, position and dimensions of the surround obstacles as well as a movement prediction in a close future. A non-restrictive estimative for the speed and direction of the ASV is calculated by mapping a conflict zone, determined by the course of the vehicle and the distance to obstacles that is used to avoid imminent dangerous situations. A set of simulations demonstrates the ability of this method to safely circumvent obstacles in several scenarios with different weather conditions.

2018

Comparative Study of Visual Odometry and SLAM Techniques

Authors
Gaspar, AR; Nunes, A; Pinto, A; Matos, A;

Publication
Advances in Intelligent Systems and Computing

Abstract
The use of the odometry and SLAM visual methods in autonomous vehicles has been growing. Optical sensors provide valuable information from the scenario that enhance the navigation of autonomous vehicles. Although several visual techniques are already available in the literature, their performance could be significantly affected by the scene captured by the optical sensor. In this context, this paper presents a comparative analysis of three monocular visual odometry methods and three stereo SLAM techniques. The advantages, particularities and performance of each technique are discussed, to provide information that is relevant for the development of new research and novel robotic applications. © Springer International Publishing AG 2018.

2018

Urban@CRAS dataset: Benchmarking of visual odometry and SLAM techniques

Authors
Gaspar, AR; Nunes, A; Pinto, AM; Matos, A;

Publication
Robotics and Autonomous Systems

Abstract

Supervised
thesis

2017

Navegação e mapeamento subaquáticos simultâneos

Author
Ana Rita da Silva Gaspar

Institution
UP-FEUP

2017

Mapeamento e odometria visual em ambiente subáquatico

Author
Alexandra Pereira Nunes

Institution
UP-FEUP

2016

Inspeção e verificação da correta assemblagem/combinação de peças em linhas de produção

Author
Ricardo Ferreira da Silva

Institution
UP-FEUP