Toward a mission value for subsea search with bottom-type variability

We propose a value function that can be used to evaluate candidate search paths for mobile sensor agents that seek to find specific objects. Our work is motivated by subsea applications where the mobile sensor agent surveys the seafloor using sonar. We presume that typical sensor performance characteristics are known, including probability of detection and probability of false alarm. Since variations in the environment can affect sensor performance, we also address the case that a stochastic description of the environment is available.