Site is still under construction. Math is still under review.
Mass of the arms are exaggerated to show the effect they have on the ROV
The most one can do is turn on or off the motors.
Notice that the motor behaves sinusoidally. After one full cycle, the motor switches sign to bring the device back to original position.
Viscous damping is preset, and can only be turned on or off
Abstract
This project is at the intersection of research and international student collaboration, with a focus on sub-sea vehicles.
Norway conducts operations on a variety of structures in the North Sea; e.g. oilrigs, monopole windmills, subsea trees.
These structures often require subsea installation, observation, and maintenance.
Research and technology that can improve the efficiency of these operations are of high interest to the nation.
A remotely operated vehicle (ROV) can assist in these operations.
However, the ROV pilot must observe and adjust the vehicle and its motion in accordance with its task, but modified due to impending forces.
Automation of this motion is the desired goal. This paper researches the motion of an ROV induced by the motion of the robotic manipulators, motor torques, and fluid buoyancy.
The research leverages a new method in engineering dynamics: the Moving Frame Method (MFM).
Lie Group Theory and Cartan’s notion of moving frames are the foundation of the MFM.
This research extends previous work in significant ways. This research accounts for the motor torques, fluid viscosity and the mass of the manipulator's arms.
Interactive visualization on hand-held devices is also an integral part of this research.
The Web Graphics Library (WebGL) is a JavaScript API for rendering interactive 3D and 2D graphics within any compatible web browser without the use of plug-ins.
This work visualizes the results, interactively, on 3D web pages, viewable on cell phones using WebGL.
This work invites further research into improved numerical methods, solid/fluid interaction and the design of Autonomous Underwater Vehicles (AUV).
AUVs beckon an era of Artificial Intelligence when machines think, communicate and learn. Rapidly deployable software implementations will be essential to this task.
This paper demonstrates the MFM clears the path toward such technological innovations.