Underwater SLAM: Challenges, state of the art, algorithms and a new biologically-inspired approach

Guth, Felipe; Silveira, Luan; Botelho, Silvia Silva da Costa; Drews, Paul; Ballester, Pedro

doi:10.1109/biorob.2014.6913908

Cited by 40 publications

(21 citation statements)

References 24 publications

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“…The apparatus is composed of surface buoys equipped with ultra-short baseline transducers (USBL) tied up with GPS receivers. Another frequently employed method is visual odometry Fraundorfer, 2011, Scaramuzza andFraundorfer, 2012), from optical or acoustic imaging in addition to SLAM algorithms see (Guth et al, 2014) and references therein, but it is not suited to static acquisitions. A simpler problem is the relative positioning of MSS data, for which the more commonly used algorithm is ICP (Dobke et al, 2013, Drap et al, 2011 or its robust version.…”

Section: Related Workmentioning

confidence: 99%

Building a 3d Reference Model for Canal Tunnel Surveying Using Sonar and Laser Scanning

Moisan

Charbonnier

Foucher

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission V KEY WORDS: 3D Bathymetry, Data processing and 3D Modeling, Reference control and accuracy assessment ABSTRACT:Maintaining canal tunnels is not only a matter of cultural and historical preservation, but also a commercial necessity and a security issue. This contribution adresses the problem of building a full 3D reference model of a canal tunnel by merging SONAR (for underwater data recording) and LASER data (for the above-water parts). Although both scanning devices produce point clouds, their properties are rather different. In particular, SONAR data are very noisy and their processing raises several issues related to the device capacities, the acquisition setup and the tubular shape of the tunnel. The proposed methodology relies on a denoising step by meshing, followed by the registration of SONAR data with the geo-referenced LASER data. Since there is no overlap between point clouds, a 3-step procedure is proposed to robustly estimate the registration parameters. In this paper, we report a first experimental survey, which concerned the entrance of a canal tunnel. The obtained results are promising and the analysis of the method raises several improvement directions that will help obtaining more accurate models, in a more automated fashion, in the limits of the involved technology.

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Section: Related Workmentioning

confidence: 99%

Building a 3d Reference Model for Canal Tunnel Surveying Using Sonar and Laser Scanning

Moisan

Charbonnier

Foucher

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

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“…The next steps will focus on creating a global and topological representation of the environment, expand the topological description to other sensors to fuse data and obtain a more precise description of the environment, evaluate the proposal on a SLAM framework like (Guth et al, ; Silveira et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…The ability to self‐localize and identify an unknown environment using its sensor readings is one of the most important challenges for the AUVs. Methods to solve these problems are called simultaneous localization and mapping (SLAM; Durrant‐Whyte & Bailey, ; Guth, Silveira, Botelho, Drews, & Ballester, ). One of the key issues to solve the SLAM problem is how to detect previously visited areas, which are called loop closure .…”

Section: Introductionmentioning

confidence: 99%

Underwater place recognition using forward‐looking sonar images: A topological approach

Santos

Zaffari

Ribeiro

et al. 2018

Journal of Field Robotics

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Autonomous underwater vehicles are a prominent tool for underwater exploration because they can access dangerous places avoiding the risks for the human beings.However, the autonomous navigation still a challenge due to the characteristics of the environment that decrease the performance of the sensor and the robot perception.In this context, this paper proposes a loop closure detector addressed to the simultaneous localization and mapping problem at semistructured environments using acoustic images acquired by forward-looking sonars. The images are segmented by an adaptative approach based on the acoustic beams analysis. A pose-invariant topological graph is build to represent the relationship between image features. The loop closure detection is achieved using a graph comparison. The approach is evaluated in a real environment at a marina. The results reveal all loop closures of the data set are detected with a high precision and present an invariant to image rotation.

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“…However, very few work has been achieved in underwater robotics where the semantic knowledge of the environment could be applied, for instance, to predict changes and to make high-level decisions. In fact, the mapping problem in underwater robots has been addressed typically by only using geometric information with sonar or Red-Green-Blue (RGB) sensors [3,4,5]. …”

Section: Introductionmentioning

confidence: 99%

Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

Santos

Ribeiro

Núñez

et al. 2017

Sensors

Self Cite

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The submarine exploration using robots has been increasing in recent years. The automation of tasks such as monitoring, inspection, and underwater maintenance requires the understanding of the robot’s environment. The object recognition in the scene is becoming a critical issue for these systems. On this work, an underwater object classification pipeline applied in acoustic images acquired by Forward-Looking Sonar (FLS) are studied. The object segmentation combines thresholding, connected pixels searching and peak of intensity analyzing techniques. The object descriptor extract intensity and geometric features of the detected objects. A comparison between the Support Vector Machine, K-Nearest Neighbors, and Random Trees classifiers are presented. An open-source tool was developed to annotate and classify the objects and evaluate their classification performance. The proposed method efficiently segments and classifies the structures in the scene using a real dataset acquired by an underwater vehicle in a harbor area. Experimental results demonstrate the robustness and accuracy of the method described in this paper.

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Underwater SLAM: Challenges, state of the art, algorithms and a new biologically-inspired approach

Cited by 40 publications

References 24 publications

Building a 3d Reference Model for Canal Tunnel Surveying Using Sonar and Laser Scanning

Building a 3d Reference Model for Canal Tunnel Surveying Using Sonar and Laser Scanning

Underwater place recognition using forward‐looking sonar images: A topological approach

Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

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