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360‐degree visual detection and target tracking on an autonomous surface vehicle
Author(s) -
Wolf Michael T.,
Assad Christopher,
Kuwata Yoshiaki,
Howard Andrew,
Aghazarian Hrand,
Zhu David,
Lu Thomas,
TrebiOllennu Ashitey,
Huntsberger Terry
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.20371
Subject(s) - unmanned surface vehicle , computer vision , computer science , artificial intelligence , propulsion , real time computing , tracking (education) , field of view , human–computer interaction , engineering , marine engineering , aerospace engineering , psychology , pedagogy
This paper describes perception and planning systems of an autonomous sea surface vehicle (ASV) whose goal is to detect and track other vessels at medium to long ranges and execute responses to determine whether the vessel is adversarial. The Jet Propulsion Laboratory (JPL) has developed a tightly integrated system called CARACaS (Control Architecture for Robotic Agent Command and Sensing) that blends the sensing, planning, and behavior autonomy necessary for such missions. Two patrol scenarios are addressed here: one in which the ASV patrols a large harbor region and checks for vessels near a fixed asset on each pass and one in which the ASV circles a fixed asset and intercepts approaching vessels. This paper focuses on the ASV's central perception and situation awareness system, dubbed Surface Autonomous Visual Analysis and Tracking (SAVAnT), which receives images from an omnidirectional camera head, identifies objects of interest in these images, and probabilistically tracks the objects' presence over time, even as they may exist outside of the vehicle's sensor range. The integrated CARACaS/SAVAnT system has been implemented on U.S. Navy experimental ASVs and tested in on‐water field demonstrations. © 2010 Wiley Periodicals, Inc.