AAAI Publications, Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence

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Improvement of Multi-AUV Cooperation through Teammate Verification
Michael Novitzky

Last modified: 2011-08-24

Abstract


Current methods for multi-AUV cooperation suffer in low communication environments. State of the art methods employ auctioneering or planning to determine a single AUV'task. These systems require communication to update models of teammates and tasks for efficient task selection. Most strategies assume a teammate is inoperable if a communication timeout is reached which reduces overall team efficiency. Including teammate prediction has been shown to mitigate efficiency degeneration due to low communication. However, there is no verification of a predicted teammate's task other than through eventual communication. A possible verification tool is behavior recognition. Current behavior recognition utilizes either overhead sensors or post mission analysis to track robot trajectories in order to infer their internal state. A system in which an AUV is capable of sensing a teammate, for example through a forward-looking sonar, and deducing it's behavior along with contextual information, such as location, will enable an AUV to determine that teammate's current task in the overall mission. This will allow for an accurate update of that teammate's model allowing the AUV to more efficiently determine its own next task rather than relying only on communication. This position paper posits that multi-AUV cooperation efficiency will improve in low communication environments with the combination of robust teammate prediction along with verification using behavior recognition.

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