A Topological Descriptor of Forward Looking Sonar Images for Navigation and Mapping

Machado, Mauro Luís da Silva; Zaffari, Guilherme B.; Ballester, Pedro; Drews-Jr, Paulo L. J.; Botelho, Silvia Silva da Costa

doi:10.1007/978-3-319-47247-8_8

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…This method extends some previous works (dos Santos, Ballester, Zaffari, Drews, & Botelho, ; dos Santos et al, ; Machado, Zaffari, Ballester, Drews, & Botelho, ; Machado, Zaffari, Ribeiro, Drews, & Botelho, ) with adaptations on the image segmentation and on the graph comparison approaches. Also, a more detailed description of the methodology and new results evaluating the proposal with data set ARACATI 2014 (Silveira et al, ) and the new data set ARACATI 2017 are presented.…”

Section: Introductionsupporting

confidence: 70%

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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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Section: Introductionsupporting

confidence: 70%

“…This study presented a loop closure detector for underwater SLAM problem that uses only visual data from a FLS. Giving continuity of previous works (dos Santos et al, , ; Machado, Zaffari, et al, ; Machado et al, ). The main idea is the topological description of the environment using graphs.…”

Section: Discussionmentioning

confidence: 83%

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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show abstract

“…The proposed study shows how objects can be detected and recognized in the scene allowing a robot to build a map. In addition, it can be integrated with the topological graphs proposed in [11], allowing the construction of more reliable maps for the localization problem, since it would be possible to establish a reliability relation between the objects and their behavior in the environment. For example, static objects such as stones and poles have more confidence than dynamic objects, which change their position over time, such as fish, boats, and swimmers, for the localization problem.…”

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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Object Recognition and Semantic Mapping for Underwater Vehicles Using Sonar Data

Santos

Drews

Núñez

et al. 2017

J Intell Robot Syst

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A Topological Descriptor of Forward Looking Sonar Images for Navigation and Mapping

Cited by 6 publications

References 16 publications

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

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

Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

Object Recognition and Semantic Mapping for Underwater Vehicles Using Sonar Data

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