Exploration of Underwater Volcano Teisi by Autonomous Underwater Vehicle ""R-One Robot""

Kenji Nagahashi;  ; Takashi Obara; Tamaki Ura;

doi:10.20965/jrm.2002.p0157

Exploration of Underwater Volcano Teisi by Autonomous Underwater Vehicle ""R-One Robot""

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2002.p0157 ◽

2002 ◽

Vol 14 (2) ◽

pp. 157-161 ◽

Cited By ~ 2

Author(s):

Kenji Nagahashi ◽

◽

Takashi Obara ◽

Tamaki Ura ◽

Keyword(s):

Autonomous Underwater Vehicle ◽

Underwater Vehicle ◽

Research Vessel ◽

Side Scan Sonar

This paper presents the exploration of underwater volcano (Teisi Knoll, Ito City, Shizuoka Pref.) by an Autonomous Underwater Vehicle (AUV) ""R-One Robot"" in October 2000. The ""R-One Robot"" was launched from the research vessel (R/V) Kaiyo in the scheduled submerging area, autonomously ascertained the direction for diving into the sea, navigated precisely passing through all way points, and lastly, surfaced right on the point as programmed. The robot succeeded in taking acoustics photographs of the crater by Side Scan Sonar on the bottom of the robot.

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Side Scan Sonar Modeling for Maritime Robotic Operations

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.152-154.1195 ◽

2012 ◽

Vol 152-154 ◽

pp. 1195-1201

Author(s):

Kuan Meng Tan ◽

Tien Fu Lu ◽

Amir Anvar

Keyword(s):

Autonomous Underwater Vehicle ◽

Underwater Vehicle ◽

Simulation Framework ◽

Test Bed ◽

Side Scan Sonar ◽

Sensor Model ◽

Sonar Sensor ◽

Key Aspects ◽

The University ◽

Sensor Modeling

One of the key aspects in designing an Autonomous Underwater Vehicle (AUV) simulation framework is sensor modeling. This paper presents specifically the underwater sonar sensor modeling structure used in the proposed AUV simulation framework. This sensor model covers the mathematical aspects from the field of acoustics which mimics real world sensors. Simplified sonar signal models are widely used however rarely discussed in the literature. Based on this designed simulation framework, simple scenario using different sonar configuration is shown and discussed. This paper shows the formulation of a typical side-scan sonar with emphasis on the assumptions which leads to the simplification of the sonar model. The sonar sensor model is built based on a developed AUV test-bed which was done previously in the University of Adelaide.

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How much fish is hidden in the surface and bottom acoustic blind zones?

ICES Journal of Marine Science ◽

10.1093/icesjms/fsp136 ◽

2009 ◽

Vol 66 (6) ◽

pp. 1355-1363 ◽

Cited By ~ 21

Author(s):

Carla Scalabrin ◽

Christian Marfia ◽

Jean Boucher

Keyword(s):

Continental Shelf ◽

Autonomous Underwater Vehicle ◽

Distribution Patterns ◽

Underwater Vehicle ◽

Fish Distribution ◽

Scattering Coefficient ◽

Research Vessel ◽

Bay Of Biscay ◽

Acoustic Surveys ◽

Scientific Payload

Abstract Scalabrin, C., Marfia, C., and Boucher, J. 2009. How much fish is hidden in the surface and bottom acoustic blind zones? – ICES Journal of Marine Science, 66: 1355–1363. This paper presents results from the ALLEGRO-07 survey that was carried out from 1 to 15 September 2007 across the continental shelf in the Bay of Biscay by the RV “Thalassa”. The main objectives were to conduct experiments with a medium-sized, autonomous underwater vehicle (AUV) equipped with a fishery-acoustic scientific payload. This was needed to overcome the difficulties of sampling the surface and bottom blind zones, which are inaccessible to conventional, vessel-mounted transducers used for acoustic surveys in the Bay of Biscay. The AUV acoustic datasets from four dives were compared with those from the research vessel. The results were expressed for the nautical-area-scattering coefficient (sA) and biomass estimates. The AUV provided higher sA measurements than did the vessel. For particular environmental and fish-distribution patterns, the biomass estimated by the AUV was more than ten times that estimated by the vessel alone. The results presented indicate the magnitude of the error that may occur in acoustic surveys, if the biomass in the two blind zones is undetected.

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