scholarly journals Test Results of the Long Baseline Navigation Solutions under a Large a Priori Position Uncertainty

2022 ◽  
Vol 1215 (1) ◽  
pp. 012006
Author(s):  
V.V. Bogomolov
Keyword(s):  
Autonomous Underwater Vehicles ◽  
A Priori ◽  
Underwater Vehicles ◽  
Posteriori Probability ◽  
Global Maximum ◽  
Test Results ◽  
Final Solution ◽  
Position Uncertainty ◽  
Modified Method ◽  
Long Baseline

Abstract A method is proposed for long baseline navigation of autonomous underwater vehicles (AUV) to be used in the case of a large a priori position uncertainty. The new modified method is based on the iterated Kalman filter (IKF) working with different initial linearization points. The final solution is calculated by clustering and weighting the IKF results. This approach allows position estimates to be determined in accordance with the global maximum of posteriori probability density of coordinates. The test results obtained with the use of three beacons and an underwater vehicle are presented.

scholarly journals Active SLAM for Autonomous Underwater Exploration

2019 ◽  
Vol 11 (23) ◽  
pp. 2827 ◽  
Author(s):  
Narcís Palomeras ◽  
Marc Carreras ◽  
Juan Andrade-Cetto
Keyword(s):  
Autonomous Underwater Vehicles ◽  
A Priori ◽  
Underwater Vehicles ◽  
View Planning ◽  
Localization And Mapping ◽  
Entropy Reduction ◽  
Graph Slam ◽  
Slam Algorithm ◽  
Iterative Closest Point Algorithm ◽  
Active Localization

Exploration of a complex underwater environment without an a priori map is beyond the state of the art for autonomous underwater vehicles (AUVs). Despite several efforts regarding simultaneous localization and mapping (SLAM) and view planning, there is no exploration framework, tailored to underwater vehicles, that faces exploration combining mapping, active localization, and view planning in a unified way. We propose an exploration framework, based on an active SLAM strategy, that combines three main elements: a view planner, an iterative closest point algorithm (ICP)-based pose-graph SLAM algorithm, and an action selection mechanism that makes use of the joint map and state entropy reduction. To demonstrate the benefits of the active SLAM strategy, several tests were conducted with the Girona 500 AUV, both in simulation and in the real world. The article shows how the proposed framework makes it possible to plan exploratory trajectories that keep the vehicle’s uncertainty bounded; thus, creating more consistent maps.

scholarly journals A Behavior-Based Mission Planner for Cooperative Autonomous Underwater Vehicles†

2012 ◽  
Vol 46 (2) ◽  
pp. 32-44 ◽  
Author(s):  
Laura Sorbi ◽  
Graziano Pio De Capua ◽  
Jean-Guy Fontaine ◽  
Laura Toni
Keyword(s):  
Autonomous Underwater Vehicles ◽  
A Priori ◽  
Underwater Vehicles ◽  
Fixed Target ◽  
Marine Research ◽  
Detection And Tracking ◽  
Mobile Target ◽  
Overall Performance ◽  
Behavior Based ◽  
Unknown Area

AbstractDue to its applications in marine research, oceanographic, and undersea exploration, autonomous underwater vehicles (AUVs) and the related control algorithms recently have been under intense investigation. In this work, we address target detection and tracking issues, proposing a control strategy that is able to benefit from the cooperation among robots within the fleet. In particular, we introduce a behavior-based planner for cooperative AUVs, proposing an algorithm that is able to search and recognize targets in both static and dynamic scenarios. With no a priori information about the surrounding environment, robots cover an unknown area with the goal of finding objects of interest. When a target is found, the AUVs’ goal is to classify (fixed target) or track (mobile target) the target, with no information about target trajectory and with formation constraints. Results demonstrate the good overall performance of the proposed algorithm in both scenarios.

scholarly journals A Single-Way Ranging Localization of AUVs Based on PSO of Outliers Elimination

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xinnan Fan ◽  
Zhongjian Wu ◽  
Jianjun Ni ◽  
Chengming Luo
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Time Of Arrival ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Simulation Experiments ◽  
Range Measurements ◽  
Acoustic Localization ◽  
Long Baseline ◽  
Key Factor

Localization of autonomous underwater vehicles (AUVs) is a very important and challenging task for the AUVs applications. In long baseline underwater acoustic localization networks, the accuracy of single-way range measurements is the key factor for the precision of localization of AUVs, whether it is based on the way of time of arrival (TOA), time difference of arrival (TDOA), or angle of arrival (AOA). The single-way range measurements do not depend on water quality and can be taken from long distances; however, there are some limitations which exist in these measurements, such as the disturbance of the unknown current velocity and the outliers caused by sensors and errors of algorithm. To deal with these problems, an AUV self-localization algorithm based on particle swarm optimization (PSO) of outliers elimination is proposed, which improves the performance of angle of arrival (AOA) localization algorithm by taking account of effects of the current on the positioning accuracy and eliminating possible outliers during the localization process. Some simulation experiments are carried out to illustrate the performance of the proposed method compared with another localization algorithm.

An Approach to Tagging Objects of Interest in Oceanic Environments Through the Use of an AUV

2017 ◽  
Author(s):  
Benjamin Waltuch ◽  
Elizabeth Astle ◽  
Eric Mirante ◽  
Brent Cornwall ◽  
James McCusker ◽  
...  
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Underwater Robotics ◽  
Test Results ◽  
Remotely Operated Vehicle ◽  
Neutral Buoyancy ◽  
Wide Range ◽  
Novel Design ◽  
Lengthy Process ◽  
The Ideal

In the field of underwater robotics, Autonomous Underwater Vehicles (AUV) have made many advancements in operating depth, mission endurance, and acoustic range making them the ideal vehicle for surveying and searching for any Object of Interest (OOI) over large areas of water. The downside to this technology is that the operator must wait for the vehicle’s mission to end to determine whether an OOI has been identified. Additionally, if an OOI is identified this object will need to be found again. The solution to this lengthy process is to equip the AUV with a suite of Underwater Locator Beacons (ULB) which can be deployed and anchored next to any positively identified OOI. This way, the operator can be actively listening for the pinging frequency of a deployed ULB where then a secondary Remotely Operated Vehicle (ROV) can be launched to retrieve or further investigate the OOI while the AUV continues its search and tag. This paper presents the design and test of a ULB deployment system that would be implemented into an AUV. An AUV is sensitive to changes in weight, therefore this novel design leverages the concepts of Archimedes Principle by preserving neutral buoyancy pre- and post-deployment of the ULB. Upon deployment, the ULB will be capable of securely anchoring itself in a wide range of seabed environments. To test the design described above, a custom ROV has been fabricated with the sole purpose of transporting the ULB deployment system to operating depth. The paper describes in detail both the test results from the ULB deployment system and a design for implementation into an AUV.

Observability Analysis for MAUVs Cooperative Navigation System Based on Moving Long Baseline

2013 ◽  
Vol 475-476 ◽  
pp. 609-615
Author(s):  
Peng Ma ◽  
Fu Bin Zhang ◽  
De Min Xu ◽  
Shao Kun Yang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Simulation Experiments ◽  
Cooperative Navigation ◽  
Long Baseline ◽  
Simulation Results ◽  
Moving Long Baseline ◽  
Theoretical Results

This paper addresses the observability problem of 2D Multiple Autonomous Underwater Vehicles (MAUVs) cooperative navigation system. We derive the conditions to keep the local weak observability of navigation system using the Lie derivatives, and characterize the unobservable trajectories of AUVs. We design a series of simulation experiments using the Extended Kalman Filter (EKF) to verify the theoretical results. Finally, the simulation results show that the good performance of navigation system can be presented if avoiding the unobservable trajectories of AUVs.

scholarly journals Path Planning for Underwater Information Gathering Based on Genetic Algorithms and Data Stochastic Models

2021 ◽  
Vol 9 (11) ◽  
pp. 1183
Author(s):  
Matteo Bresciani ◽  
Francesco Ruscio ◽  
Simone Tani ◽  
Giovanni Peralta ◽  
Andrea Timperi ◽  
...  
Keyword(s):  
Path Planning ◽  
Information Content ◽  
Autonomous Underwater Vehicles ◽  
A Priori ◽  
Posidonia Oceanica ◽  
Underwater Vehicles ◽  
Information Gathering ◽  
Technological Developments ◽  
Path Planner ◽  
Areas Of Interest

Recent technological developments have paved the way to the employment of Autonomous Underwater Vehicles (AUVs) for monitoring and exploration activities of marine environments. Traditionally, in information gathering scenarios for monitoring purposes, AUVs follow predefined paths that are not efficient in terms of information content and energy consumption. Informative Path Planning (IPP) represents a valid alternative, defining the path that maximises the gathered information. This work proposes a Genetic Path Planner (GPP), which consists in an IPP strategy based on a Genetic Algorithm, with the aim of generating a path that simultaneously maximises the information gathered and the coverage of the inspected area. The proposed approach has been tested offline for monitoring and inspection applications of Posidonia Oceanica (PO) in three different geographical areas. The a priori knowledge about the presence of PO, in probabilistic terms, has been modelled utilising a Gaussian Process (GP), trained on real marine data. The GP estimate has then been exploited to retrieve an information content of each position in the areas of interest. A comparison with other two IPP approaches has been carried out to assess the performance of the proposed algorithm.

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