TY - GEN
T1 - AUV Tri-TON 2
T2 - 2014 IEEE/OES Autonomous Underwater Vehicles, AUV 2014
AU - Maki, Toshihiro
AU - Sato, Yoshiki
AU - Matsuda, Takumi
AU - Shiroku, Reyes Tatsuru
AU - Sakamaki, Takashi
PY - 2015/3/3
Y1 - 2015/3/3
N2 - The AUV Tri-TON 2 was built in 2013 under the governmental project to develop instruments to estimate ore reserves in underwater hydrothermal deposits, after the success of the prototype AUV Tri-TON [1]. The vehicle has two suites of imaging instruments looking forward and downward directions, in order to obtain dense, large-area 3D image of hydrothermal vent fields. The vehicle can follow rugged surface of hydrothermal vent fields at close range of less than 2.0 m. Although the vehicle is not equipped with an inertial navigation system (INS), the vehicle can estimate its position in real-time with a precision enough for rough photo-mosaicing, owing to the mutual acoustic positioning with a seafloor station. The vehicle has a strong ability of real-time path-planning to obtain a full-coverage 3D image of a rough, unknown seafloor in a single deployment [2]. The performance of the vehicle was verified through a series of sea experiments. At the first experiment, the vehicle succeeded in imaging seafloor with the area of 14 × 10 m. Then, the vehicle was deployed to hydrothermal vent field at Irabu Knoll in Okinawa Trough with the depth of 1,840m.
AB - The AUV Tri-TON 2 was built in 2013 under the governmental project to develop instruments to estimate ore reserves in underwater hydrothermal deposits, after the success of the prototype AUV Tri-TON [1]. The vehicle has two suites of imaging instruments looking forward and downward directions, in order to obtain dense, large-area 3D image of hydrothermal vent fields. The vehicle can follow rugged surface of hydrothermal vent fields at close range of less than 2.0 m. Although the vehicle is not equipped with an inertial navigation system (INS), the vehicle can estimate its position in real-time with a precision enough for rough photo-mosaicing, owing to the mutual acoustic positioning with a seafloor station. The vehicle has a strong ability of real-time path-planning to obtain a full-coverage 3D image of a rough, unknown seafloor in a single deployment [2]. The performance of the vehicle was verified through a series of sea experiments. At the first experiment, the vehicle succeeded in imaging seafloor with the area of 14 × 10 m. Then, the vehicle was deployed to hydrothermal vent field at Irabu Knoll in Okinawa Trough with the depth of 1,840m.
UR - http://www.scopus.com/inward/record.url?scp=84961386046&partnerID=8YFLogxK
U2 - 10.1109/AUV.2014.7054422
DO - 10.1109/AUV.2014.7054422
M3 - Conference contribution
AN - SCOPUS:84961386046
T3 - 2014 IEEE/OES Autonomous Underwater Vehicles, AUV 2014
BT - 2014 IEEE/OES Autonomous Underwater Vehicles, AUV 2014
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 6 October 2014 through 9 October 2014
ER -