Towards Real-Time Search Planning in Subsea Environments
This addresses the challenge of efficient target search in subsea environments for applications like marine exploration or surveillance, though it is incremental in improving real-time planning.
The paper tackles the problem of computing real-time search paths for locating unknown targets on the seafloor, showing that near-optimal paths can be computed in real-time with comparable effectiveness to optimal but infeasible ones, as demonstrated in numerical experiments using sonar data from Boston Harbor.
We address the challenge of computing search paths in real-time for subsea applications where the goal is to locate an unknown number of targets on the seafloor. Our approach maximizes a formal definition of search effectiveness given finite search effort. We account for false positive measurements and variation in the performance of the search sensor due to geographic variation of the seafloor. We compare near-optimal search paths that can be computed in real-time with optimal search paths for which real-time computation is infeasible. We show how sonar data acquired for locating targets at a specific location can also be used to characterize the performance of the search sonar at that location. Our approach is illustrated with numerical experiments where search paths are planned using sonar data previously acquired from Boston Harbor.