A Deterministic Search Approach for Solving Stochastic Drone Search and Rescue Planning Without Communications

In disaster relief efforts, delivering aid to areas with no communication poses a significant challenge. Unmanned aerial vehicles (UAVs) can be utilized to deliver aid kits to survivors in hard-to-reach areas; unfortunately, in some areas, lack of communication and infrastructure presents a key problem. In this paper, we address a stochastic planning problem of planning for a set of UAVs that deliver aid kits to areas that lack communications, where we do not know in advance the locations where aid kits need to be delivered, but rather have probabilistic information about the locations of aid targets. Our main insight is that, despite the stochastic nature of this problem, we can solve it through deterministic search by monitoring the expected reward for each partial solution. This insight enables the application of deterministic planning techniques, empirically demonstrating a notable improvement in efficiency and response speed. Our approach presents a promising solution to addressing the challenge of delivering aid in regions with limited radio infrastructure, as well as similar planning problems.