Abstract
It is usually difficult to use underwater robots for mapping, reconnaissance, and mine-clearing tasks in shallow water (10 to 80 foot depth) ocean environments. The shallow water environment is characterized by strong, intermittent wave surge which requires robot behaviors that are capable of riding out the surge and then repositioning the platform and re- acquiring the objects being sensed. The shallow water area is also characterized by water that is murky, making optical sensors useless for long range search, and which produces multiple paths for sonar returns, giving errant range readings. Teleoperation from a remote surface platform is not effective due to the rapid changes in the environment. A more promising approach would place reactive intelligence on-board the robot. This paper describes such an approach which uses high frequency acoustic and vision sensing and a situated reasoning software architecture to provide task-achieving capability to an underwater robot in a shallow water environment. The approach is demonstrated in the context of a shallow water marking task wherein a robot must locate and navigate to a moored object in shallow water depths, attach a buoyant marker, and then return to a destination location. The approach seeks to integrate selective perception with robust transit and hovering behaviors to overcome the natural problems associated with shallow water environments.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
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