CRAS

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http://localhost:4000/handle/123456789/39
This performs research and development activities in autonomous robotic systems, mobile robotics and multi-robot mobile systems for inspection, monitoring and mapping, with applications in security, energy, environment, aquaculture, oceanography, marine biology, resource extraction, among other sectors. These activities are supported by research in perception, navigation, control, localization, coordination, and automatic data acquisition and processing.

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Browsing CRAS by Author "5158"
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    Autonomous Tracking of a Horizontal Boundary
    ( 2014) Nuno Cruz ; Aníbal Matos ; 5155 ; 5158
    The ability to employ autonomous vehicles to find and track the boundary between two different water masses can increase the efficiency in waterborne data collection, by concentrating measurements in the most relevant regions and capturing detailed spacial and temporal variations. In this paper we provide a guidance mechanism to enable an autonomous vehicle to find and track the steepest gradient of a scalar field in the horizontal plane. The main innovation in our approach is the mechanism to adapt the orientation of the crossings to the local curvature of the boundary, so that the vehicle can keep tracking the gradient regardless of its horizontal orientation. As an example, we show how the algorithms can be used to find and track the boundary of a dredged navigation channel, using only altimeter measurements.
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    Cooperative deep water seafloor mapping with heterogeneous robotic platforms
    ( 2017) Pinto,A ; Dias,A ; Melo,J ; Alfredo Martins ; Abreu,N ; Almeida,J ; Almeida,R ; José Carlos Alves ; Carlos Filipe Gonçalves ; Ferreira,H ; Ferreira,B ; Nuno Cruz ; Silva,E ; Aníbal Matos ; Hugo Miguel Silva ; Eduardo Silva ; Vitor Hugo Pinto ; 5570 ; 258 ; 5155 ; 5158 ; 5429 ; 5473 ; 6852 ; 6920
    This paper describes the PISCES system, an integrated approach for fully autonomous mapping of large areas of the ocean in deep waters. A deep water AUV will use an acoustic navigation system to compute is position with bounded error. The range limitation will be overcome by a moving baseline scheme, with the acoustic sources installed in robotic surface vessels with previously combined trajectories. In order to save power, all systems will have synchronized clocks and implement the One Way Travel Time scheme. The mapping system will be a combination of an off-the-shelf MBES with a new long range bathymetry system, with a source on a moving surface vessel and the receivers on board the AUV. The system is being prepared to participate in round one of the XPRIZE challenge. © 2017 Marine Technology Society.
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    Critical object recognition in underwater environment
    ( 2019) Alexandra Nunes ; Ana Gaspar ; Aníbal Matos ; 5158 ; 6868 ; 6869
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    DART - A portable deep water hovering AUV
    ( 2017) Aníbal Matos ; Bruno Miguel Ferreira ; Almeida,RM ; Nuno Cruz ; 5158 ; 5238 ; 5155
    Autonomous Underwater Vehicles are remarkable machines that revolutionized the collection of data at sea. There are many examples of highly operational man-portable vehicles for shallow waters, but there was no similar solution for deep water operations. This paper describes the development of a portable, modular, hovering AUV for deep water operations. The vehicle has little over 50kg, 2.4m of length, and a depth rating of 4000m. The first version of the vehicle has been assembled, it has gone through the initial tests in water tanks, and it is being prepared for the first operations at sea. © 2017 Marine Technology Society.
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    Evaluation of Bags of Binary Words for Place Recognition in Challenging Scenarios
    ( 2021) Ana Gaspar ; Alexandra Nunes ; Aníbal Matos ; 5158 ; 6868 ; 6869
    To perform autonomous tasks, robots in real-world environments must be able to navigate in dynamic and unknown spaces. To do so, they must recognize previously seen places to compensate for accumulated positional deviations. This task requires effective identification of recovered landmarks to produce a consistent map, and the use of binary descriptors is increasing, especially because of their compact representation. The visual Bag-of-Words (BoW) algorithm is one of the most commonly used techniques to perform appearance-based loop closure detection quickly and robustly. Therefore, this paper presents a behavioral evaluation of a conventional BoW scheme based on Oriented FAST and Rotated BRIEF (ORB) features for image similarity detection in challenging scenarios. For each scenario, full-indexing vocabularies are created to model the operating environment and evaluate the performance for recognizing previously seen places similar to online approaches. Experiments were conducted on multiple public datasets containing scene changes, perceptual aliasing conditions, or dynamic elements. The Bag of Binary Words technique shows a good balance to deal with such severe conditions at a low computational cost. © 2021 IEEE.
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    An Hierarchical Architecture for Docking Autonomous Surface Vehicles
    ( 2019) Aníbal Matos ; Andry Maykol Pinto ; Pedro Nuno ; Renato Jorge Silva ; 7626 ; 5446 ; 5158 ; 7627
    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.
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    MARESye: A hybrid imaging system for underwater robotic applications
    ( 2020) Aníbal Matos ; Andry Maykol Pinto ; 5446 ; 5158
    This article presents an innovative hybrid imaging system that provides dense and accurate 3D information from harsh underwater environments. The proposed system is called MARESye and captures the advantages of both active and passive imaging methods: multiple light stripe range (LSR) and a photometric stereo (PS) technique, respectively. This hybrid approach fuses information from these techniques through a data-driven formulation to extend the measurement range and to produce high density 3D estimations in dynamic underwater environments. This hybrid system is driven by a gating timing approach to reduce the impact of several photometric issues related to the underwater environments such as, diffuse reflection, water turbidity and non-uniform illumination. Moreover, MARESye synchronizes and matches the acquisition of images with sub-sea phenomena which leads to clear pictures (with a high signal-to-noise ratio). Results conducted in realistic environments showed that MARESye is able to provide reliable, high density and accurate 3D data. Moreover, the experiments demonstrated that the performance of MARESye is less affected by sub-sea conditions since the SSIM index was 0.655 in high turbidity waters. Conventional imaging techniques obtained 0.328 in similar testing conditions. Therefore, the proposed system represents a valuable contribution for the inspection of maritime structures as well as for the navigation procedures of autonomous underwater vehicles during close range operations.
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    A mosaicking technique for object identification in underwater environments
    ( 2019) Alexandra Nunes ; Ana Gaspar ; Andry Maykol Pinto ; Aníbal Matos ; 5446 ; 6869 ; 6868 ; 5158
    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.
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    Occupancy Grid Mapping from 2D SONAR Data for Underwater Scenes
    ( 2021) Alexandra Nunes ; Ana Gaspar ; Aníbal Matos ; 5158 ; 6868 ; 6869
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    A PHD Filter for Tracking Multiple AUVs
    ( 2014) Aníbal Matos ; Melo,J ; 5158
    In this paper we address the problem of tracking multiple AUVs using acoustic signals. Using For this challenging scenario, we propose to use a Probability Hypothesis Density Filter and present a suitable implementation of the Sequential Monte Carlo PHD filter. It will be demonstrated that a particle filter implementation of the aforementioned filter can be used to successfully track multiple AUVs, changing in number over time, using range measurements from the vehicles to a set of acoustic beacons. Simulation results will be presented that allow to evaluate the performance of the filter.
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    REX 16-Robotic Exercises 2016 Multi-robot field trials
    ( 2019) Marques,F ; Bruno Miguel Ferreira ; Aníbal Matos ; Lobo,V ; Marques,MM ; Mendonca,R ; Ramalho,T ; Castelao,I ; Simoes,N ; 5238 ; 5158
    Nowadays, one of the problems associated with Unmanned Systems is the gap between research community and end-users. In order to emend this problem, the Portuguese Navy Research Center (CINAV) conducts the REX 2016 (Robotic Exercises). This paper describes the trials that were presented in this exercise, divided in two phases. The first phase happened at the Naval Base in Lisbon, with the support of divers and RHIBs (Rigid-Hulled Inflatable Boats), and the second phase, also with divers' support, at the coast of Lisbon-Cascais. It counted with many participants and research groups, including INESC-TEC, UNINOVA, TEKEVER and UAVISION. There are several advantages of doing this exercise, including for the Portuguese Navy, but also for partners. For the Navy, because it is an opportunity of being in contact with recent market technologies and researches. On the other hand, it is an opportunity for the partners to test their systems in a real environment, which usually is a difficult action to accomplish. Therefore, the paper describes three of the most relevant experiments: underwater docking stations, UAV and USV cooperation and Tracking targets from UAVs.
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    A Safety Monitoring Model for a Faulty Mobile Robot
    ( 2018) Andry Maykol Pinto ; Leite,A ; Aníbal Matos ; 5158 ; 5446
    The continued development of mobile robots (MR) must be accompanied by an increase in robotics' safety measures. Not only must MR be capable of detecting and diagnosing faults, they should also be capable of understanding when the dangers of a mission, to themselves and the surrounding environment, warrant the abandonment of their endeavors. Analysis of fault detection and diagnosis techniques helps shed light on the challenges of the robotic field, while also showing a lack of research in autonomous decision-making tools. This paper proposes a new skill-based architecture for mobile robots, together with a novel risk assessment and decision-making model to overcome the difficulties currently felt in autonomous robot design.
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    Simultaneous Underwater Navigation and Mapping
    ( 2019) Aníbal Matos ; Ana Gaspar ; 5158 ; 6868
    The use of underwater autonomous vehicles has been growing, allowing the performance of tasks that cause inherent risks to Human, namely in inspection processes near to structures. With growth in usage of systems with autonomous navigation, visual acquisition methods have also gotten more developed because, they have appealing cost and they also show interesting results when operate at a short distance. It is possible to improve the quality of navigation through visual SLAM techniques which can map and locate simultaneously and its key aspect is the detection of revisited areas. These techniques are not usually applied to underwater scenarios and, therefore, its performance in environment is unknown. The paper presents a more reliable navigation system for underwater vehicles, resorting to some visual SLAM techniques from literature. The results, conducted in a realistic scenario, demonstrated the ability of the system to be applied to underwater environment.
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    Three-Dimensional Mapping in Underwater Environment
    ( 2019) Alexandra Nunes ; Aníbal Matos ; 5158 ; 6869
    Autonomous underwater vehicles are applied in diverse fields, namely in tasks that are risky for human beings to perform, as optical inspection for the purpose of structures quality control. Optical sensors are more appealing cost and they supply a larger quantity of data. Lasers can be used to reconstruct structures in three dimensions, along with cameras, which create a faithful representation of the environment. However, in this context a visual approach was used and the paper presents a method that can put together the three-dimensional information that has been harvested over time, combining also RGB information for surface reconstruction. The map construction follows the motion estimated by a odometry method previously selected from the literature. Experiments conducted using real scenario show that the proposed solution is able to provide a reliable map for objects and even the seafloor.
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    Tracking multiple Autonomous Underwater Vehicles
    ( 2019) Aníbal Matos ; Melo,J ; 5158
    In this paper we present a novel method for the acoustic tracking of multiple Autonomous Underwater Vehicles. While the problem of tracking a single moving vehicle has been addressed in the literature, tracking multiple vehicles is a problem that has been overlooked, mostly due to the inherent difficulties on data association with traditional acoustic localization networks. The proposed approach is based on a Probability Hypothesis Density Filter, thus overcoming the data association problem. Our tracker is able not only to successfully estimate the positions of the vehicles, but also their velocities. Moreover, the tracker estimates are labelled, thus providing a way to establish track continuity of the targets. Using real word data, our method is experimentally validated and the performance of the tracker is evaluated. © 2018 Springer Science+Business Media, LLC, part of Springer Nature
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    Urban@CRAS dataset: Benchmarking of visual odometry and SLAM techniques
    ( 2018) Ana Gaspar ; Aníbal Matos ; Andry Maykol Pinto ; Alexandra Nunes ; 6868 ; 5446 ; 5158 ; 6869