A Forward-Looking Sonar-Based System for Underwater Mosaicing and Acoustic Odometry

Franchi, Matteo; Ridolfi, Alessandro; Zacchini, Leonardo

doi:10.1109/auv.2018.8729795

Cited by 20 publications

(11 citation statements)

References 21 publications

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“…After the end of the competition, a 2D mosaic of the area around the structure (see Figures 5, 9), namely an underwater plastic pipe assembly with the aim of representing the (flooded) lower section of the plant, was performed. For a detailed description of the acoustic mosaic formation process, the interested reader can refer to Franchi et al (2018). The proposed FIGURE 9 | The structure placed on the sea bottom (Ferri et al, 2017).…”

Section: Payload Processing Resultsmentioning

confidence: 99%

“…Furthermore, the real dimensions of the underwater structure (which were a priori known) are in accordance with the size that can be obtained from Figure 10. Indeed, structure dimensions are about 2.20 × 3.20 × 1.20 m, whereas the obtained ones are 2.20×3.46 m. More information concerning the conversion from pixels to meters is presented by the authors in Franchi et al (2018).…”

Section: Payload Processing Resultsmentioning

confidence: 99%

“…To locate the exact position of the detected targets, starting from the known position of the vehicle, an imaging geometry model needs to be defined and the reader can refer to Franchi et al ( 2018 ) for more information. In few words, exploiting the work of Johannsson et al ( 2010 ), Ferreira et al ( 2014 ), Hurtós et al ( 2015 ), and Walter ( 2008 ), a simplified linear model, where the FLS can be treated as an orthographic camera, is adopted.…”

Section: Feelhippo Auv: Software Architecturementioning

confidence: 99%

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Underwater Robotics Competitions: The European Robotics League Emergency Robots Experience With FeelHippo AUV

et al. 2020

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Underwater robots are nowadays employed for many different applications; during the last decades, a wide variety of robotic vehicles have been developed by both companies and research institutes, different in shape, size, navigation system, and payload. While the market needs to constitute the real benchmark for commercial vehicles, novel approaches developed during research projects represent the standard for academia and research bodies. An interesting opportunity for the performance comparison of autonomous vehicles lies in robotics competitions, which serve as an useful testbed for state-of-the-art underwater technologies and a chance for the constructive evaluation of strengths and weaknesses of the participating platforms. In this framework, over the last few years, the Department of Industrial Engineering of the University of Florence participated in multiple robotics competitions, employing different vehicles. In particular, in September 2017 the team from the University of Florence took part in the European Robotics League Emergency Robots competition held in Piombino (Italy) using FeelHippo AUV, a compact and lightweight Autonomous Underwater Vehicle (AUV). Despite its size, FeelHippo AUV possesses a complete navigation system, able to offer good navigation accuracy, and diverse payload acquisition and analysis capabilities. This paper reports the main field results obtained by the team during the competition, with the aim of showing how it is possible to achieve satisfying performance (in terms of both navigation precision and payload data acquisition and processing) even with small-size vehicles such as FeelHippo AUV.

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Section: Payload Processing Resultsmentioning

confidence: 99%

Section: Payload Processing Resultsmentioning

confidence: 99%

Section: Feelhippo Auv: Software Architecturementioning

confidence: 99%

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Underwater Robotics Competitions: The European Robotics League Emergency Robots Experience With FeelHippo AUV

et al. 2020

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“…Convolutional neural network (CNNs) can be considered the state-of-the-art performance of image classification tasks also in the maritime domain. Many authors propose their usage for both side-looking sonar [15,16] and FLS [17] achieving good results with well-trained networks.A considerable problem of the underwater domain is the difficulty of obtaining precisely geo-referenced images collected by a sensor and, consequently, the difficulty of subsequently locating found objects. The lack of GPS into the water makes necessary the use of solutions [18,19] based on one or more surface gateways and systems of underwater positioning and communication such as ultra-short baseline (USBL), short baseline (SBL) or long baseline (LBL) techniques.…”

Section: Robots For Seabed Explorationmentioning

confidence: 99%

Marine Robots for Underwater Surveillance

et al. 2020

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Purpose of Review The paper reviews the role of marine robots, in particular unmanned vehicles, in underwater surveillance, i.e. the control and monitoring of an area of competence aimed at identifying potential threats in support of homeland defence, antiterrorism, force protection and Explosive Ordnance Disposal (EOD). Recent Findings The paper explores separately robotic missions for identification and classification of threats lying on the seabed (e.g. EOD) and anti-intrusion robotic systems. The current main scientific challenge is identified in terms of enhancing autonomy and team/swarm mission capabilities by improving interoperability among robotic vehicles and providing communication networking capabilities, a non-trivial task, giving the severe limitations in bandwidth and latency of acoustic underwater messaging. Summary The work is intended to be a critical guide to the recent prolific bibliography on the topic, providing pointers to the main recent advancements in the field, and to give also a set of references in terms of mission and stakeholders' requirements (port authorities, coastal guards, navies).

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“…The detailed process to obtain linear speed estimations from a pair of FLS images is beyond the goal of this paper, but the authors have already presented a complete description (Franchi et al, 2018(Franchi et al, , 2019(Franchi et al, , 2020. Briefly speaking, the complete process, which is depicted in Figure 3, is divided into three main steps:…”

Section: Kinematic and Dynamic Modeling For Auvsmentioning

confidence: 99%

Underwater navigation with 2D forward looking SONAR: An adaptive unscented Kalman filter‐based strategy for AUVs

Franchi

Ridolfi

Allotta

2020

Journal of Field Robotics

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One of the most significant challenges in the underwater domain is to retrieve the autonomous underwater vehicle (AUV) position within the surrounding environment. Indeed, reliable navigation systems are fundamental to perform complex tasks and missions. Most of the navigation filters for AUVs are based on Bayesian estimators such as the linear Kalman Filter (KF), the extended KF, the unscented KF, or the particle filter where, usually, different instruments including a Doppler velocity log (DVL) contribute to the localization task. The usage of forward-looking SONARs (FLS) in navigation-aiding is, most of the time, devoted to limiting the navigation drift of the AUV by using simultaneous localization and mapping methods. Therefore, these devices are commonly employed with a standard navigation sensors set comprising an attitude heading reference system and a DVL. In this contribution, the authors propose a novel navigation strategy specifically tailored to AUVs based on an adaptive unscented KF, where linear speed estimations are obtained with a 2D FLS instead of with a DVL and therefore promoting the employment of FLSs as an aid for underwater navigation. The marine robotics community could gain significant benefits from reliable navigation achieved with an FLS-based navigation architecture. Most importantly, a single FLS can be used for imaging-related applications (i.e., sonograms acquisition) and navigation, where, instead, different dedicated devices are currently employed for the two tasks. Smaller AUVs usually possess reduced payload carrying capabilities; thus, multitasking use of onboard sensors, which leads to compactness, is a desirable feature. Navigation data obtained during sea trials performed in La Spezia (Italy) at the NATO STO Centre for Maritime Research and Experimentation has been used for offline validation. Afterward, the online results of real autonomous underwater missions undertaken in La Spezia (Italy) and at Vulcano Island, Messina (Italy), are reported.

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A Forward-Looking Sonar-Based System for Underwater Mosaicing and Acoustic Odometry

Cited by 20 publications

References 21 publications

Underwater Robotics Competitions: The European Robotics League Emergency Robots Experience With FeelHippo AUV

Underwater Robotics Competitions: The European Robotics League Emergency Robots Experience With FeelHippo AUV

Marine Robots for Underwater Surveillance

Underwater navigation with 2D forward looking SONAR: An adaptive unscented Kalman filter‐based strategy for AUVs

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