AUV behavior recognition using behavior histograms, HMMs, and CRFs. Issue 2 (March 2014)

• Record Type: Journal Article
• Authors: Novitzky, Michael; Pippin, Charles; Collins, Thomas R.; Balch, Tucker R.; West, Michael E.
• Is Part Of: Robotica. Volume 32:Issue 2(2014)
• Page Start: 291
• Page End: 304
• Publication Date: 2014-03
• Subjects: Robots -- Periodicals; 629.89205
• DOI: 10.1017/S0263574713001306
• Languages: English
• ISSNs: 0263-5747

Abstract

<abstract abstract-type="normal"> <title>SUMMARY</title> <p>This paper focuses on behavior recognition in an underwater application as a substitute for communicating through acoustic transmissions, which can be unreliable. The importance of this work is that sensor information regarding other agents can be leveraged to perform behavior recognition, which is activity recognition of robots performing specific programmed behaviors, and task-assignment. This work illustrates the use of Behavior Histograms, Hidden Markov Models (HMMs), and Conditional Random Fields (CRFs) to perform behavior recognition. We present challenges associated with using each behavior recognition technique along with results on individually selected test trajectories, from simulated and real sonar data, and real-time recognition through a simulated mission.</p> </abstract>