Efficient Reacquire and Identify Path Planning Over Large Areas

An important task in maritime search and inspection involves re-acquiring and identifying underwater objects by surveying the objects from multiple angles. Because of false contacts related to clutter on the sea floor, the objects are often detected in dramatically different densities in a given area. Previously developed methods to plan survey paths on groups of contacts led to efficient paths when the contacts occur in close proximity, but inefficient paths when the objects occur over large distances. We present a planning algorithm to generate an efficient path to survey objects from multiple angles that is independent of the density of the objects. The algorithm leverages the previously-developed algorithms for surveying objects from multiple directions, coupled with density-based spatial clustering of applications with noise (DBSCAN) clustering and ant colony optimization techniques.