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Development of a Simulator and Training System for Remotely Operated Vehicle Pilots

The maneuver of ROV requires considerable pilot skill which is a product of physical and mental practice over a long period of time. However, with the limitations of ROV safety, the availability and high cost of deploying equipment, most of ROV pilots gain the necessary skill through on-the-job training. In this study, we developed a simulation system for ROV pilot training and mission planning. This system is implemented in C++ with the cross-platform OpenGL for 3D graphics. It equips with a scene editor allowing the user to build complex 3D geometric objects from simpler primitives. This editor allows the user to change settings of ambient light intensity, visibility, current speed, and seafloor topography for fulfilling specific training requirements. As well, the user can translate and rotate the entire 3D scene and look at it from different vantage point. Besides, this system provides the user with simple commands for mission planning. For realistically simulating the dynamic behavior of the ROV, the nonlinear hydrodynamic equations of motion of the ROV with six degrees of freedom are applied to describe its motion. Moreover, this system is built with the capability of collision detection for evaluating the collision response of ROV. During the training process, the data engine records all navigation data which can be retrieved and played after conducting a training course. The animation playback function exactly reproduces the scenario that occurs during the period of training. It presents the trainee with the opportunity to review the whole operation scenario. Besides, experiments were designed based on the Taguchi Method to study the effects of different factors on ROV pilot performance. The factors selected for evaluation include ROV trajectory display, underwater visibility, ROV positioning error, and current speed. We found that underwater visibility has the greatest influence on ROV pilot performance, next are ROV positioning error and ROV trajectory display, then the current speed. This result will be helpful in rating the level of difficulty of the training.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0728104-144427
Date28 July 2004
CreatorsHsiao, Yu-hung
ContributorsHsin-hung Chen, Chau-chang Wang, Jen-hwa Guo, Ming-chung Fang
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0728104-144427
Rightsoff_campus_withheld, Copyright information available at source archive

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