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Stereo vision–based navigation for autonomous surface vessels
Author(s) -
Huntsberger Terry,
Aghazarian Hrand,
Howard Andrew,
Trotz David C.
Publication year - 2010
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.20380
Subject(s) - computer vision , artificial intelligence , navigation system , stereopsis , computer science , key (lock) , machine vision , fire control system , unmanned surface vehicle , obstacle avoidance , stereo cameras , real time computing , engineering , robot , mobile robot , fire control , geography , computer security , cartography , marine engineering
This paper describes a stereo vision–based system for autonomous navigation in maritime environments. The system consists of two key components. The Hammerhead vision system detects geometric hazards (i.e., objects above the waterline) and generates both grid‐based hazard maps and discrete contact lists (objects with position and velocity). The R4SA (robust, real‐time, reconfigurable, robotic system architecture) control system uses these inputs to implement sensor‐based navigation behaviors, including static obstacle avoidance and dynamic target following. As far as the published literature is concerned, this stereo vision–based system is the first fielded system that is tailored for high‐speed, autonomous maritime operation on smaller boats. In this paper, we present a description and experimental analysis of the Hammerhead vision system, along with key elements of the R4SA control system. We describe the integration of these systems onto a number of high‐speed unmanned surface vessels and present experimental results for the combined vision‐based navigation system. © 2010 Wiley Periodicals, Inc.