The algorithm of autonomous underwater vehicles /AUVs/ trajectories planning for mapping of oceanographic data is considered in the paper. The problem of this research consists in adaptive data sampling by single AUV or group of vehicles for further high-precision mapping of environment parameters under restriction of whole given area covering. For simulation a bathymetry scalar field was considered, which is given by a digital elevation model. Some simulation results of considered algorithm operation are supplemented.
Consider the problem of 2D distributed oceanographic scalar field mapping like temperature in horizontal plane or bathymetry. Traditional sampling methods using vessels and towed sensors are in general expensive and do not provide detailed aquatic area coverage. Using this technology, area of interest is covered by nets of tacks. However, this method can take much time if the purpose of research is a detailed survey of inhomogeneous underwater environment. In this case it would be more appropriate to use an AUV with according algorithms of trajectory planning, designed for more fast and precise solution of this problem. The problem can be resolved by taking more samples in fast-changing data areas and few samples in slow-changing data areas. Our task consists in an algorithm designing, which builds such adaptive trajectory for AUV that covers the aquatic square without gaps. The basic idea is to build a trajectory, consisting of meander patterns of different ―levels‖. Patterns of larger level use smaller step between tacks. An AUV control system has to make a decision if the current meander level should be changed according to measured data. A simulation was performed to verify of considered algorithm efficiency. Scalar bathymetric field, provided by digital elevation model /DEM/, was used for survey. Algorithm effectiveness was estimated by time of operation and resulting map precision for used bathymetric field.