Location-Aware, Flexible Task Management for Collaborating Unmanned Autonomous Vehicles

Author

Wang, Meng ; Zhao, Yang ; Doboli, Alex

Author_Institution

Dept. of Electr. & Comput. Eng., State Univ. of New York at Stony Brook, Stony Brook, NY, USA

fYear

2009

fDate

July 29 2009-Aug. 1 2009

Firstpage

59

Lastpage

66

Abstract

Unmanned autonomous vehicles (UAVs) are emerging as a breakthrough concept in technology. A main challenge related to UAV control is devising flexible strategies with predictable performance in hard-to-predict conditions. This paper proposes an approach to performance predictive collaborative control of UAVs operating in environments with fixed targets. The paper offers detailed experimental insight on the quality, scalability and computational complexity of the proposed method.

Keywords

computational complexity; mobile robots; predictive control; remotely operated vehicles; computational complexity; flexible task management; location-awareness; performance predictive collaborative control; unmanned autonomous vehicle; Adaptive systems; Collaboration; Communication system control; Decision making; Mobile robots; NASA; Processor scheduling; Remotely operated vehicles; Unmanned aerial vehicles; Vehicle dynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Adaptive Hardware and Systems, 2009. AHS 2009. NASA/ESA Conference on

Conference_Location

San Francisco, CA

Print_ISBN

978-0-7695-3714-6

Type

conf

DOI

10.1109/AHS.2009.67

Filename

5325472