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Online View Planning for Inspecting Unexplored Underwater Structures

In this letter, we propose a method to automate the exploration of unknown underwater structures for autonomous underwater vehicles (AUVs). The proposed algorithm iteratively incorporates exteroceptive sensor data and replans the next-best-view in order to fully map an underwater structure. This approach does not require prior environment information. However, a safe exploration depth and the exploration area (defined by a bounding box, parameterized by its size, location, and resolution) must be provided by the user. The algorithm operates online by iteratively conducting the following three tasks: (1) Profiling sonar data are first incorporated into a 2-D grid map, where voxels are labeled according to their state (a voxel can be labeled as empty, unseen, occluded, occplane, occupied, or viewed). (2) Useful viewpoints to continue exploration are generated according to the map. (3) A safe path is generated to guide the robot toward the next viewpoint location. Two sensors are used in this approach: a scanning profiling sonar, which is used to build an occupancy map of the surroundings, and an optical camera, which acquires optical data of the scene. Finally, in order to demonstrate the feasibility of our approach, we provide real-world results using the Sparus II AUV

This work was supported by the EXCELLABUST and ARCHROV Projects under Grants H2020-TWINN-2015, CSA, ID: 691980, and DPI2014-57746-C3-3-R. The work of E. Vidal was supported by the Spanish Government through Ph.D. grant FPU14/05493

© IEEE Robotics and Automation Letters, 2017, vol. 2, núm. 3, p.1436-1443

Institute of Electrical and Electronics Engineers (IEEE)

Autor: Vidal Garcia, Eduard
Hernández Vega, Juan David
Istenič, Klemen
Carreras Pérez, Marc
Data: 17 febrer 2017
Resum: In this letter, we propose a method to automate the exploration of unknown underwater structures for autonomous underwater vehicles (AUVs). The proposed algorithm iteratively incorporates exteroceptive sensor data and replans the next-best-view in order to fully map an underwater structure. This approach does not require prior environment information. However, a safe exploration depth and the exploration area (defined by a bounding box, parameterized by its size, location, and resolution) must be provided by the user. The algorithm operates online by iteratively conducting the following three tasks: (1) Profiling sonar data are first incorporated into a 2-D grid map, where voxels are labeled according to their state (a voxel can be labeled as empty, unseen, occluded, occplane, occupied, or viewed). (2) Useful viewpoints to continue exploration are generated according to the map. (3) A safe path is generated to guide the robot toward the next viewpoint location. Two sensors are used in this approach: a scanning profiling sonar, which is used to build an occupancy map of the surroundings, and an optical camera, which acquires optical data of the scene. Finally, in order to demonstrate the feasibility of our approach, we provide real-world results using the Sparus II AUV
This work was supported by the EXCELLABUST and ARCHROV Projects under Grants H2020-TWINN-2015, CSA, ID: 691980, and DPI2014-57746-C3-3-R. The work of E. Vidal was supported by the Spanish Government through Ph.D. grant FPU14/05493
Format: application/pdf
Cita: https://doi.org/10.1109/LRA.2017.2671415
ISSN: 2377-3766
Accés al document: http://hdl.handle.net/10256/14452
Llenguatge: eng
Editor: Institute of Electrical and Electronics Engineers (IEEE)
Col·lecció: MINECO/PE 2015-2017/DPI2014-57746-C3-3-R
Reproducció digital del document publicat a: https://doi.org/10.1109/LRA.2017.2671415
Articles publicats (D-ATC)
info:eu-repo/grantAgreement/EC/H2020/691980
És part de: © IEEE Robotics and Automation Letters, 2017, vol. 2, núm. 3, p.1436-1443
Drets: Tots els drets reservats
Matèria: Vehicles submergibles
Submersibles
Robots autònoms
Autonomous robots
Algorismes computacionals
Computer algorithms
Títol: Online View Planning for Inspecting Unexplored Underwater Structures
Tipus: info:eu-repo/semantics/article
Repositori: DUGiDocs

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