Study on the Mechanical Characteristics of a Towing Docking Device for USV Self-Recovering AUVs

Meng, Long; Gu, Hui; Yang, Lin; Bai, Gongxun; Tang, Dongsheng

doi:10.1109/oceanse.2019.8866991

Cited by 3 publications

(1 citation statement)

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“…The team recognized that the capability for the unmanned launch and recovery of an AUV could be the deciding factor for the success of the mapping campaign, where this kind of solution was not popular or accessible as an off-the-shelf solution. Meng et al [21] and Gu et al [22] presented studies on a device towed underwater for the recovery of an AUV. Solutions based on towing have been also proposed by other Shell Ocean Discovery XPRIZE participants [23], but their reliability in some cases might be not sufficient for open-sea operations.…”

Section: Data Acquisition Systemmentioning

confidence: 99%

The Autonomous Underwater Vehicle Integrated with the Unmanned Surface Vessel Mapping the Southern Ionian Sea. The Winning Technology Solution of the Shell Ocean Discovery XPRIZE

et al. 2020

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The methods of data collection, processing, and assessment of the quality of the results of a survey conducted at the Southern Ionian Sea off the Messinian Peninsula, Greece are presented. Data were collected by the GEBCO-Nippon Foundation Alumni Team, competing in the Shell Ocean Discovery XPRIZE, during the Final Round of the competition. Data acquisition was conducted by the means of unmanned vehicles only. The mapping system was composed of a single deep water AUV (Autonomous Underwater Vehicle), equipped with a high-resolution synthetic aperture sonar HISAS 1032 and multibeam echosounder EM 2040, partnered with a USV (Unmanned Surface Vessel). The USV provided positioning data as well as mapping the seafloor from the surface, using a hull-mounted multibeam echosounder EM 304. Bathymetry and imagery data were collected for 24 h and then processed for 48 h, with the extensive use of cloud technology and automatic data processing. Finally, all datasets were combined to generate a 5-m resolution bathymetric surface, as an example of the deep-water mapping capabilities of the unmanned vehicles' cooperation and their sensors' integration.The ocean floor is the most remote and difficult part of our planet, yet to be explored. Due to the extreme conditions facing exploration, the majority of the world's ocean floor is still unmapped [1,2]. Modern mapping techniques, based on the acoustic technology, allow us the possibility to collect bathymetric and water column data, but the survey process is slow and expensive. The majority of present-day surveying efforts go into the busier, shallow waters for the purpose of safety of navigation. While this represents an understandable and necessary approach, it results in the majority of the deep ocean still being unmapped. The overall shape of the global ocean floor is an estimation based on the satellite altimetry technique [3] and interpolation between sparse acoustic measurements.The American foundation XPRIZE announced in 2015 that the next award will go to those who come up with the solution for faster, detailed mapping of the ocean floor, without exposing humans to the harsh sea environment. That was the beginning of the Shell Ocean Discovery XPRIZE. To compete in the final round of the Shell Ocean Discovery XPRIZE, each team had to present the solution for collecting bathymetric data and imagery data and successfully complete Round 1 in 2017. During the second round a year later, the bathymetric data collection had to achieve depths of up to 4000 m, with a vertical resolution of 0.5 m and a horizontal resolution of 5 m. The imagery needed to include images presenting recognizable geological, biological, or archaeological features on the seabed. The solution had to be autonomous or remote controlled, but there must have been no human inside the survey area, and no physical link between the devices and the mission control location. The mapping system, with all its elements, had to fit into one standard 40-ft shipping container. The minimum coverage to be achieved during t...

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Section: Data Acquisition Systemmentioning

confidence: 99%