
Proceedings Paper
A unified cooperative control architecture for UAV missionsFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
In this paper, we propose a unified cooperative control architecture (UCCA) that supports effective cooperation of
Unmanned Aerial Vehicles (UAVs) and learning capabilities for UAV missions. Main features of the proposed UCCA
include: i) it has a modular structure; each function module focuses on a particular type of task and provide services to
other function modules through well defined interfaces; ii) it allows the efficient sharing of UAV control and onboard
resources by the function modules and is able to effectively handle simultaneously multiple objectives in the UAV
operation; iii) it facilitates the cooperation among different function modules; iv) it supports effective cooperation among
multiple UAVs on a mission's tasks, v) an objective driven learning approach is also supported, which allows UAVs to
systematically explore uncertain mission environments to increase the level of situation awareness for the achievement
of their mission/task objectives.
Paper Details
Date Published: 17 May 2012
PDF: 9 pages
Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83920X (17 May 2012); doi: 10.1117/12.919793
Published in SPIE Proceedings Vol. 8392:
Signal Processing, Sensor Fusion, and Target Recognition XXI
Ivan Kadar, Editor(s)
PDF: 9 pages
Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83920X (17 May 2012); doi: 10.1117/12.919793
Show Author Affiliations
Xin Tian, I-Fusion Technology, Inc. (United States)
Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Genshe Chen, I-Fusion Technologies, Inc (United States)
Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Genshe Chen, I-Fusion Technologies, Inc (United States)
Erik Blasch, Air Force Research Lab. (United States)
Khanh Pham, Air Force Research Lab. (United States)
Khanh Pham, Air Force Research Lab. (United States)
Published in SPIE Proceedings Vol. 8392:
Signal Processing, Sensor Fusion, and Target Recognition XXI
Ivan Kadar, Editor(s)
© SPIE. Terms of Use
