  Survivors stranded during floods tend to seek refuge on dry land. It is
important to search for these survivors and help them reach safety as quickly
as possible. The terrain in such situations however, is heavily damaged and
restricts the movement of emergency personnel towards these survivors.
Therefore, it is advantageous to utilize Unmanned Aerial Vehicles (UAVs) in
cooperation with on-ground first responders to aid search and rescue efforts.
In this article we demonstrate an implementation and improvement of the
weight-based path planning algorithm using an off-the-shelf UAV. The
coordinates of the survivor and their heading is reported by an on-ground
observer to the UAV to generate a weighted map of the surroundings for
exploration. Each coordinate in the map is assigned a weight which dictates the
priority of exploration. These waypoints are then sorted on the basis of their
weights to arrive at an ordered list for exploration by the UAV. We developed
the model in MATLAB, followed by prototyping on Robot Operating System (ROS)
using a 3DR Iris quadcopter. We tested the model on an off-the-shelf UAV by
utilizing the MAVROS and MAVLINK capabilities of ROS. During the implementation
of the algorithm on the UAV, several additional factors such as unreliable GPS
signals and limited field of view which could effect the performance of the
model were in effect, despite which the algorithm performed fairly well. We
compared our model with conventional algorithms described in the literature,
and showed that our implementation outperforms them.
