Abstract
As autonomous ocean vehicles become more affordable and reliable, applications of multivehicle teams become more feasible. Cooperative vehicle target tracking is a promising application since in many sport, military, and biological endeavors cooperative strategies have proven themselves to be advantageous over noncooperative strategies. The sophistication of winning human team interactions indicates the challenge inherent in programming a fleet of autonomous vehicles to work cooperatively to effectively and efficiently accomplish a goal. For a multivehicle team operating in the continuous and transient ocean environment, meeting this challenge involves optimizing a high-dimensional parameter space, even more so in cases when the target has the ability to make intelligent choices to avoid being tracked. In this chapter, recent progress to construct a theoretical framework and recent applications for maritime surveillance are presented. A methodology is developed that can help bridge the gap between the top-down view starting with theoretical concepts and the bottom-up view dealing with all details of real experimentation and execution at sea.
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Abbreviations
- AIS:
-
automatic identification system
- AUV:
-
autonomous underwater vehicle
- CA:
-
cellular automata
- CE:
-
control and estimation
- DEC-POMDP:
-
decentralized partially observable Markov decision process
- HF:
-
high frequency
- LFCTT:
-
low-frequency cooperative target tracking
- MAS:
-
multiagent system
- PDF:
-
probability density function
- PGM:
-
probabilistic graphical model
- POMDP:
-
partially observable Markov decision process
- POSG:
-
partially observable stochastic games
- SAT:
-
satellite communication
- UAV:
-
unmanned aerial vehicle
- UHF:
-
ultra high frequency
- VHF:
-
very high frequency
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Ehlers, F. (2016). Cooperative Vehicle Target Tracking. In: Dhanak, M.R., Xiros, N.I. (eds) Springer Handbook of Ocean Engineering. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-319-16649-0_22
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