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Publicações

Publicações por Alfredo Martins

2020

Teaching Robotics with a Simulator Environment Developed for the Autonomous Driving Competition

Autores
Fernandes, D; Pinheiro, F; Dias, A; Martins, A; Almeida, J; Silva, E;

Publicação
ROBOTICS IN EDUCATION: CURRENT RESEARCH AND INNOVATIONS

Abstract
Teaching robotics based on challenge of our daily lives is always more motivating for students and teachers. Several competitions of self-driving have emerged recently, challenging students and researchers to develop solutions addressing the autonomous driving systems. The Portuguese Festival Nacional de Rob ' otica (FNR) Autonomous Driving Competition is one of those examples. Even though the competition is an exciting challenger, it requires the development of real robots, which implies several limitations that may discourage the students and compromise a fluid teaching process. The simulation can contribute to overcome this limitation and can assume an important role as a tool, providing an effortless and costless solution, allowing students and researchers to keep their focus on the main issues. This paper presents a simulation environment for FNR, providing an overall framework able to support the exploration of robotics topics like perception, navigation, data fusion and deep learning based on the autonomous driving competition.

2020

Underwater Localization System Combining iUSBL with Dynamic SBL in VAMOS! Trials

Autores
Almeida, J; Matias, B; Ferreira, A; Almeida, C; Martins, A; Silva, E;

Publicação
SENSORS

Abstract
Emerging opportunities in the exploration of inland water bodies, such as underwater mining of flooded open pit mines, require accurate real-time positioning of multiple underwater assets. In the mining operation scenarios, operational requirements deny the application of standard acoustic positioning techniques, posing additional challenges to the localization problem. This paper presents a novel underwater localization solution, implemented for the VAMOS! project, based on the combination of raw measurements from a short baseline (SBL) array and an inverted ultrashort baseline (iUSBL). An extended Kalman filter (EKF), fusing IMU raw measurements, pressure observations, SBL ranges, and USBL directional angles, estimates the localization of an underwater mining vehicle in 6DOF. Sensor bias and the speed of sound in the water are estimated indirectly by the filter. Moreover, in order to discard acoustic outliers, due to multipath reflections in such a confined and cluttered space, a data association layer and a dynamic SBL master selection heuristic were implemented. To demonstrate the advantage of this new technique, results obtained in the field, during the VAMOS! underwater mining field trials, are presented and discussed.

2019

Design and Development of a multi rotor UAV for Oil Spill Mitigation

Autores
Oliveira, A; Pedrosa, D; Santos, T; Dias, A; Amaral, G; Martins, A; Almeida, J; Silva, E;

Publicação
OCEANS 2019 - MARSEILLE

Abstract
Over the last few years, oil spill incidents occured with some regularity during exploration, production and transportation, causing a large economic and ecologic impact in the world community. To minimise these impacts and reduce the time response of the initial mitigation process, autonomous vehicles, such as unmanned aerial vehicles (UAV) can be used to perform oil spill monitoring and mitigation. This paper presents the design and implementation of a multirotor UAV capable of identifying and combat the oil spill, by using a release system of consortia with bacteria and nutrients. Several field tests occurred in Portugal and Spain, where the oil spill was implemented in a simulated environment, resulting in a cooperative and simultaneous manoeuvre between the vehicles.

2019

ROSM - Robotic Oil Spill Mitigation

Autores
Dias, A; Mucha, AP; Santos, T; Pedrosa, D; Amaral, G; Ferreira, H; Oliveira, A; Martins, A; Almeida, J; Almeida, CM; Ramos, S; Magalhaes, C; Carvalho, MF; Silva, E;

Publicação
OCEANS 2019 - MARSEILLE

Abstract
The overall aim of the ROSM project is the implementation of an innovative solution based on heterogeneous autonomous vehicles to tackle maritime pollution (in particular, oil spills). These solutions will be based on native microbial consortia with bioremediation capacity, and the adaptation of air and surface autonomous vehicles for in-situ release of autochthonous microorganisms (bioaugmentation) and nutrients (biostimulation). By doing so, these systems can be used as the first line of the responder to pollution incidents from several origins that may occur inside ports, around industrial and extraction facilities, or during transport activities, in a fast, efficient and low-cost way. The paper will address the development of a team of autonomous vehicles able to carry, as payload, native organisms to naturally degrade oil spills (avoiding the introduction of additional chemical or biological additives), the development of a multi-robot system able to provide a first line responses to oil spill incidents under unfavourable and harsh conditions with low human intervention, and then a decentralized cooperative planning with the ability to coordinate an efficient oil spill combat. Field tests have been performed in Leixoes Harbour in Porto and Medas, Portugal, with a simulated oil spill and validated the decentralized coordinated task between the autonomous surface vehicle (ASV) ROAZ and the unmanned aerial vehicle (UAV).

2020

MARA - A modular underwater robot for confined spaces exploration

Autores
Martins, A; Almeida, J; Almeida, C; Pereira, R; Sytnyk, D; Soares, E; Matias, B; Pereira, T; Silva, E;

Publicação
GLOBAL OCEANS 2020: SINGAPORE - U.S. GULF COAST

Abstract
This paper presents an innovative modular autonomous underwater vehicle (MARA) developed for the exploration of underwater confined spaces such as underwater caves, flooded underground mines or complex tight infrastructures in underwater environments. The particular mission scenario of exploration of flooded underground mines was used as a key driver for the robot development. The autonomous underwater vehicle is described from the mechanical, hardware and software points of view. The availability of the INESC TEC underwater systems test tank and access conditions to Porto harbour and the Urgeirica mine allows for easy robot field validation. Preliminary results are also presented and discussed.

2020

A robotic solution for NETTAG lost fishing net problem

Autores
Martins, A; Almeida, C; Lima, P; Viegas, D; Silva, J; Almeida, JM; Almeida, C; Ramos, S; Silva, E;

Publicação
GLOBAL OCEANS 2020: SINGAPORE - U.S. GULF COAST

Abstract
This paper presents an autonomous robotic system, IRIS, designed for lost fishing gear recovery. The vehicle was developed in the context of the NetTag project. This is a European Union project funded by EASME the Executive Agency for Small and Medium Enterprises addressing marine litter, and the reduction of quantity and impact of lost fishing gears in the ocean. NetTag intends to produce new technological devices for location and recovery of fishing gear and educational material about marine litter, raise awareness of fisheries industry and other stakeholders about the urgent need to combat marine litter and increase scientific knowledge on marine litter problematic, guaranteeing the engagement of fishers to adopt better practices to reduce and prevent marine litter derived from fisheries. The design of IRIS is presented in detail, addressing the mechanical design, hardware architecture, sensor system and navigation and control. Preliminary tests in tank and in controlled sea conditions are presented and ongoing developments on the recovery system are discussed.

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