Planning Autonomous Underwater Reconnaissance Operations. Bernardini, S., Fox, M., Long, D., & Ridder, B. In
abstract   bibtex   
In this paper, we focus on the task of reconnaissance in an underwater setting. The objective is to efficiently search a large area in order to identify safe passages for ships. A path is considered safe if there are no rocky regions within it as these can conceal hazards such as mines. Our approach is to decompose the area into regions which can then be allocated for seach to individual vehicles. An initial, coarse, lawnmower survey gives some indication of the make-up of the area to be searched, and the next step is to use this survey to hypothesise about the structure of the unseen areas. It is hypothesised that any as-yet unseen areas are rocky and the task of the AUVs is to disprove this hypothesis by planning efficient paths to investigate these unseen areas. We have developed a plan-based approach, reasoning about the movement of probability mass as the planned search progresses, that searches a large area very efficiently. To demonstrate the potential of our technique, we have developed a simulation based on ROS and integrated our system into the commercial "SeeByte Neptune" simulator.
@InProceedings{spark16-14,
  author =   {Sara Bernardini and Maria Fox and Derek Long and Bram Ridder},
  title =    {Planning Autonomous Underwater Reconnaissance Operations},
  abstract = {In this paper, we focus on the task of reconnaissance in an underwater setting. The objective is to efficiently search a large area in order to identify safe passages for ships. A path is considered safe if there are no rocky regions within it as these can conceal hazards such as mines. Our approach is to decompose the area into regions which can then be allocated for seach to individual vehicles. An initial, coarse, lawnmower survey gives some indication of the make-up of the area to be searched, and the next step is to use this survey to hypothesise about the structure of the unseen areas. It is hypothesised that any as-yet unseen areas are rocky and the task of the AUVs is to disprove this hypothesis by planning efficient paths to investigate these unseen areas. We have developed a plan-based approach, reasoning about the movement of probability mass as the planned search progresses, that searches a large area very efficiently. To demonstrate the potential of our technique, we have developed a simulation based on ROS and integrated our system into the commercial "SeeByte Neptune" simulator.},
  keywords = {reconnaissance AUVs, Autonomous Underwater Vehicles, Automated Planning, Temporal Planing, PDDL, POPF}
}

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