A trajectory optimization method for close range surveys of non-planar surfaces

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Abstract/Contents

Abstract
This thesis develops a trajectory optimization method for underwater robotic vehicles performing close range visual surveys of a surface. The work in this thesis is motivated by the problem of acquiring high-quality imagery of the ocean floor. The method described herein enables the systematic tradeoff of competing survey objectives, and also enables motion-constrained survey vehicles to use prior terrain data to anticipate upcoming terrain changes. In general, visual survey missions trade off image quality for trajectory smoothness. Due to light's limited penetration through water, the terrain is typically only visible within a few meters of the sea floor. Furthermore, the highest image quality occurs when the camera is pointed perpendicular to the terrain and when the camera maintains a constant altitude over the terrain. However, if a smooth trajectory is desired over rough non-planar terrain, perpendicularity and altitude uniformity must be sacrificed. No previous work has developed a systematic way of performing this tradeoff. Survey trajectories are generated by specifying a trajectory smoothness constraint, then optimally planning trajectories that maximize perpendicularity and altitude performance under the constraint. Trajectories are planned over a B-spline surface that is fit optimally to a bathymetric map of the survey area. The fitting occurs by mapping the trajectory smoothness constraint to geometric constraints on the B-spline, then solving a newly posed nonlinear constrained optimization problem. Results that compare the performance of the optimally generated trajectories against previous visual survey methods are presented. Results in the field validate the use of the method to survey sections of ocean floor in Monterey Bay, CA.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2012
Issuance monographic
Language English

Creators/Contributors

Associated with Murthy, Kiran Kumar
Associated with Stanford University, Department of Aeronautics and Astronautics
Primary advisor Rock, Stephen M
Thesis advisor Rock, Stephen M
Thesis advisor Alonso, Juan José, 1968-
Thesis advisor Enge, Per
Advisor Alonso, Juan José, 1968-
Advisor Enge, Per

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Kiran Kumar Murthy.
Note Submitted to the Department of Aeronautics and Astronautics.
Thesis Ph.D. Stanford University 2012
Location electronic resource

Access conditions

Copyright
© 2012 by Kiran Kumar Murthy
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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