Samuel Barrett's Publications

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Optimization of Multi-Attribute Tasks for Underwater Motion of Robotic Sensor Agents

Irina Goldman, Samuel Barrett, and Jeffrey V. Nickerson. Optimization of Multi-Attribute Tasks for Underwater Motion of Robotic Sensor Agents. In IEEE International Conference on Intelligence and Security Informatics, pp. 374, May 2007.

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Abstract

Target detection, identification, and tracking are tasks of great importance in counterterrorism preparations. The development of a new generation of mobile autonomous wireless robotic sensor agents provides new advanced opportunities for target monitoring and tracking. We are particularly interested in the investigation of the underwater motion of the mobile robotic sensor agents. However, the trajectory of the underwater motion of a robotic sensor agent from the initial point to the destination significantly differs from the ground motion trajectory. Firstly, an underwater vehicle is affected by the current flow and its motion strongly depends on the structure of the river (cross-section shape, bottom type, etc) or ocean. Secondly, the battery power is limited and it almost impossible to recharge the batteries while the agent is underwater. Also, the time for robotic sensor agents to reach the target may be crucial. Consequently, finding the fastest path to the destination given a water stream is important. Thus, how should cluster of underwater robotic sensors move to optimize multi-attribute tasks?

BibTeX

@INPROCEEDINGS{ISI07-Goldman,
  author={Irina Goldman and Samuel Barrett and Jeffrey V. Nickerson},
  booktitle={IEEE International Conference on Intelligence and Security Informatics},
  title={Optimization of Multi-Attribute Tasks for Underwater Motion of Robotic Sensor Agents},
  year={2007},
  month=may,
  pages={374},
  keywords={counterterrorism preparation;current flow;ground motion trajectory;mobile autonomous wireless robotic sensor agents;multiattribute task;optimization;river structure;target detection;target identification;target tracking;underwater motion;water stream;maximum principle;military systems;mobile robots;motion control;position control;target tracking;terrorism;time optimal control;},
  doi={10.1109/ISI.2007.379510},
  ISSN={},
  abstract={
    Target detection, identification, and tracking are tasks of great importance in
    counterterrorism preparations. The development of a new generation of mobile
    autonomous wireless robotic sensor agents provides new advanced opportunities
    for target monitoring and tracking. We are particularly interested in the
    investigation of the underwater motion of the mobile robotic sensor agents.
    However, the trajectory of the underwater motion of a robotic sensor
    agent from the initial point to the destination significantly differs
    from the ground motion trajectory. Firstly, an underwater vehicle is
    affected by the current flow and its motion strongly depends on the
    structure of the river (cross-section shape, bottom type, etc) or ocean.
    Secondly, the battery power is limited and it almost impossible to
    recharge the batteries while the agent is underwater. Also, the time for
    robotic sensor agents to reach the target may be crucial. Consequently,
    finding the fastest path to the destination given a water stream
    is important. Thus, how should cluster of underwater robotic
    sensors move to optimize multi-attribute tasks?
  }
}

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