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Proceedings Paper

Intelligent obstacle avoidance system for unmanned undersea vehicles in shallow water
Author(s): Keehoon Kim; Andrew A. Kostrzewski; Daniel A. Erwin
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Paper Abstract

An unmanned undersea vehicle (UUV) needs an obstacle avoidance capability to make autonomous path planning decisions for successful undersea search and survey, maritime reconnaissance, communication/navigation aids, and tracking and trailing in uncharted shallow water. Physical Optics Corporation (POC) has developed a novel autonomous UUV path optimization navigator system for real-time, robust, self-adjusting, intelligent autonomous obstacle avoidance/navigation of UUVs. The POC system is based on our proprietary fast genetic algorithm, which processes signals from on-board obstacle avoidance sonar sensors to continuously optimize the navigation path while avoiding both moving and stationary obstacles in shallow waters. The system performs autonomous obstacle avoidance, accommodating navigation parameter changes. Vehicle dynamics are also incorporated by hydrodynamic compensation.

Paper Details

Date Published: 1 September 2004
PDF: 8 pages
Proc. SPIE 5417, Unattended/Unmanned Ground, Ocean, and Air Sensor Technologies and Applications VI, (1 September 2004); doi: 10.1117/12.543447
Show Author Affiliations
Keehoon Kim, Physical Optics Corp. (United States)
Andrew A. Kostrzewski, Physical Optics Corp. (United States)
Daniel A. Erwin, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 5417:
Unattended/Unmanned Ground, Ocean, and Air Sensor Technologies and Applications VI
Edward M. Carapezza, Editor(s)

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