Online Boundary Estimation in Partially Observable Environments Using a UAV

Environmental boundary estimation is the process of bounding the region(s) where the measurement of all locations exceeds a certain threshold value. In this paper, we develop a framework for environmental boundary tracking and estimation in partially observable environments which are processed in an online manner. Dedicated sensors mounted on the vehicle are considered to be capable of on-the-spot field intensity measurements. Focusing on the limited resources of Unmanned Aerial Vehicles (UAVs), it is important to track an unknown boundary in a fast manner. Therefore, we present a motion planning strategy that enables a single UAV to estimate the boundary of a given target area while minimizing the exploration cost. To do so, we improve the conventional position controller based framework by integrating a noise canceling filter and a novel adaptive crossing angle correction scheme. The effectiveness of the proposed algorithm is demonstrated in three different simulated environments. We also analyze the performance of framework subject to various conditions.