A Distributed Framework of Autonomous Drones
for Planning and Execution of Relief Operations
during Flood Situations
1Department
of Computer Science, University of Engineering and Technology, Pakistan
2Department
of Software Engineering, University of Gujrat, Pakistan
Abstract: Every year, flood hits the world economy by billions
of dollars, costs thousands of human and animal lives, destroys a vast area of
land and crops, and displaces large populations from their homes. The flood affected
require a time-critical help, and a delay may cause the loss of precious human
lives. The ground rescue operations are difficult to carry out because of the
unavailability of transport infrastructure. However, drones, Unmanned Vehicles,
can easily navigate to the areas where road networks have been destroyed or
become ineffective. The fleet participating in the rescue operation should have
drones with different capabilities in order to make the efforts more
successful. A majority of existing systems in the literature offered a
centralized system for these drones. However, the performance of the existing
system starts decreasing as the required number of tasks increases. This
research is based on the hypothesis that a distributed intelligent method is
more effective than the centralized technique for relief operations performed
by multiple drones. The research aims to propose a distributed method that
allows a fleet of drones with diverse capabilities to communicate and
collaborate, so that the task completion rate of rescue operations could be
increased. The proposed solution consists of three main modules: 1)
communication and message transmission module that enables collaboration
between drones, 2) realignment module that allows drones to negotiate and
occupy the best position in the air to optimize the coverage area, 3) situation
monitoring module that identifies the ground situation and acts accordingly. To
validate the proposed solution, we have performed a simulation using AirSim
simulator and compared the results with the centralized system. The proposed distributed
method performed better than legacy systems. In the future, the work can be
extended using reinforcement learning and other intelligent algorithms.
Keywords: Autonomous drones, flood
relief operations, distributed systems, artificial intelligence, distributed
collaboration.
Received October 11, 2019; accepted July 14,
2020
