A forward-looking SONAR and dynamic model-based AUV navigation strategy: Preliminary validation with FeelHippo AUV

Franchi, Matteo; Ridolfi, Alessandro; Pagliai, Marco

doi:10.1016/j.oceaneng.2019.106770

Cited by 32 publications

(42 citation statements)

References 31 publications

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“…If roll and pitch variations are consistent, a tilt unit can be employed to maintain the FLS to an approximately desired configuration. Assumptions 1-5 are usually met for most of the AUVs, and they are similar to those already exploited in some of the authors' previous works Franchi et al, 2020).…”

Section: Kinematic and Dynamic Modeling For Auvsmentioning

confidence: 81%

“…In other words, if the drive command signal is low, it might not be enough to generate an actual rotation for the motors. In such a situation, the authors (Franchi et al, 2020) showed that a more thorough representation is:…”

Section: Kinematic and Dynamic Modeling For Auvsmentioning

confidence: 99%

“…More recently, similarly to optical cameras in visual-inertial navigation systems, the use of FLSs has emerged as an aid for inertial-based solutions. In Franchi et al (2019Franchi et al ( , 2020, the authors proposed a dead reckoning (DR)based underwater navigation strategy that exploits speed estimations from an FLS or a dynamic model of the AUV. To the authors' best knowledge, only similar contributions can be found in Yang and Huang (2017) and Song et al (2018).…”

mentioning

confidence: 99%

“…Here, as in Franchi et al (2020), the use of FLSs to aid underwater navigation is further promoted, giving them a more central role within the navigation framework. The presented navigation solution, able to operate without employing DVL readings, goes beyond what is already proposed by the authors in Franchi et al (2020), thus extending and enriching the authors' previous works. Indeed, in Franchi et al (2020), a simple FLSbased DR strategy is validated and only in post-processing.…”

mentioning

confidence: 99%

“…Moreover, first, the presented solution is compared offline with the one in Franchi et al (2020), showing better navigation performance. Second, it is experimentally evaluated during two different underwater tests at sea (in two different locations).…”

mentioning

confidence: 99%

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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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Section: Kinematic and Dynamic Modeling For Auvsmentioning

confidence: 81%

Section: Kinematic and Dynamic Modeling For Auvsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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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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Sensor‐driven autonomous underwater inspections: A receding‐horizon RRT‐based view planning solution for AUVs

Zacchini

Franchi

Ridolfi

2022

Journal of Field Robotics

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Autonomous Underwater Vehicles (AUVs) are used by the scientific community for various applications, from collecting well-distributed high-quality data to mapping the seafloor or exploring unknown areas. Nonpredictable environmental conditions and sensor acquisitions make the design of AUV surveys challenging even for expert operators. Multiple attempts are required, and the collected data quality is not guaranteed: The AUV passively stores the sensors' acquisitions that are then analyzed offline after its recovery. In Forward-Looking SONAR (FLS) seabed inspections, the vehicle follows lawnmower paths designed by an expert operator that considers the sensor characteristics. The performance of FLSs is affected by several environmental conditions and possible protruding objects. This paper presents a probabilistic framework for FLS-based seabed inspections that endow the AUV with the ability to autonomously conducting the survey and ensure adequate coverage of the target area. A three-dimensional probabilistic occupancy mapping system for FLS reconstructions to update the covered area map was developed. The map is used by the Coverage Path Planning (CPP) algorithm to evaluate the visibility of the viewpoints that are generated as nodes of a random tree. The Next-Best Viewpoint (NBV) is selected as the first node in the branch expected to collect more data, and the path to reach the NBV is computed using the rapidly exploring random tree (RRT*) algorithm. The sensor-driven coverage approach is used in a receding-horizon manner. The proposed Receding-Horizon Coverage Approach was validated with simulations and real prerecorded data. Finally, the framework was used online during an experimental campaign where several FLS seabed inspections were performed.

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2D Forward Looking SONAR in Underwater Navigation Aiding: an AUKF-based strategy for AUVs

2020

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A forward-looking SONAR and dynamic model-based AUV navigation strategy: Preliminary validation with FeelHippo AUV

Cited by 32 publications

References 31 publications

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

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

Sensor‐driven autonomous underwater inspections: A receding‐horizon RRT‐based view planning solution for AUVs

2D Forward Looking SONAR in Underwater Navigation Aiding: an AUKF-based strategy for AUVs

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