Cooperative control of autonomous underwater vehicles.

by Savage, Elizabeth

Abstract (Summary)
The proposed project is the simulation of a system to search for air vehicles which

have splashed-down in the ocean. The system comprises a group of 10+ autonomous

underwater vehicles, which cooperate in order to locate the aircraft. The search algorithm

used in this system is based on a quadratic Newton method and was developed

at Sandia National Laboratories. The method has already been successfully applied

to several two dimensional problems at Sandia.

The original 2D algorithm was converted to 3D and tested for robustness in the

presence of sensor error, position error and navigational error. Treating the robots as

point masses, the system was found to be robust for all such errors.

Several real-life adaptations were necessary. A round-robin communication strategy

was implemented on the system to properly simulate the dissemination of information

throughout the group. Time to convergence is delayed but the system still

functioned adequately.

Once simulations for the point masses had been exhausted, the dynamics of the

robots were included. The robot equations of motion were described using Kane's

equations. Path-planning was investigated using optimal control methods. The Variational

Calculus approach was attempted using a line search tool "fsolve" found in

Matlab and a Genetic Algorithm. A dynamic programming technique was also investigated using a method recently developed by Sandia National Laboratories. The Dynamic

Programming with Interior Points (DPIP) method was a very effcient method

for path planning and performed well in the presence of system constraints.

Finally all components of the system were integrated. The motion of the robot

exactly matched the motion of the particles, even when subjected to the same robustness

tests carried out on the point masses. This thesis provides exciting developments

for all types of cooperative projects.

Bibliographical Information:

Advisor:Hurtado, John E.; Junkins, John; Swaroop, Darbha; Valasek, John

School:Texas A&M University

School Location:USA - Texas

Source Type:Master's Thesis

Keywords:autonomous auv cooperative control dynamic programming genetic algorithms optimal underwater search


Date of Publication:05/01/2003

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