DocumentCode
1284955
Title
Robust Adaptive Markov Decision Processes: Planning with Model Uncertainty
Author
Bertuccelli, Luca F. ; Wu, Albert ; How, Jonathan P.
Volume
32
Issue
5
fYear
2012
Firstpage
96
Lastpage
109
Abstract
The ability of autonomous systems to make complex decisions is becoming an increasingly commonplace requirement for many cooperative control operations, including the management of teams of robots such as unmanned aerial vehicles (UAV). Central to this research is the requirement to optimize the vehicle decisions, such as route planning and allocation of team resources, while operating in a dynamic and uncertain environment. Even with the advent of increasingly sophisticated vehicle sensors that can improve the information about the surroundings, uncertainty remains a ubiquitous feature of UAV applications and a key issue in UAV research.
Keywords
Markov processes; adaptive control; autonomous aerial vehicles; cooperative systems; mobile robots; multi-robot systems; optimal control; path planning; resource allocation; robot vision; robust control; uncertain systems; MDP; UAV; autonomous systems; complex decision making; cooperative control operations; dynamic environment; information improvement; robotic team management; robust adaptive Markov decision processes; route planning; team resource allocation; uncertain environment; unmanned aerial vehicles; vehicle decision optimization; vehicle sensors; Dynamic scheduling; Path planning; Resource management; Robot sensing systems; Robustness; Unmanned aerial vehicles;
fLanguage
English
Journal_Title
Control Systems, IEEE
Publisher
ieee
ISSN
1066-033X
Type
jour
DOI
10.1109/MCS.2012.2205478
Filename
6302309
Link To Document