Dynamic self-Organised Algorithm for UAVS swarm
Abstract
There is an increasing interest in the use of unmanned aerial vehicles (UAVs) to offer
various services, e.g., parcels delivery medical supplies, live video recording and relay to
mention but a few. This has therefore increased the number of UAVs that fly in a given
environment. So as the UAVS move they need to be collision free. A number of collision
avoidance methods have been proposed. The need of operation in urban cities increases the
need of the best algorithm to counter act Collision between UAVs and the environment and
fellow UAVs.
Drones are also used in cases where a task can be performed more economically and or more
efficiently than if done by humans. These include remote sensing tasks where drones can be
required to form coalitions by pooling their resources to meet the service requirements at
different locations of interest in a city. During such coalition formation, finding the shortest
path from a source to a location of interest is key to efficient service delivery.
This project focuses on developing a dynamic self-organised algorithm for UAV swarm
which is to be used by the quadcopters to avoid collision between them and with the other
obstacles with in the environment where these quadcopters passes while doing their
operations. This was achieved by developing an algorithm which we used to program the
UAV quadcopters and it was initially tested with 2 UAVs then 4 UAVs and then 6 UAVs
using robotic simulator software (webots) We evaluated the performance of the algorithm by
comparing how number of quadcopter used affect the time of mission completion when
considered the sensor range distance. We also evaluated the algorithm by considering how
the speed of these quadcopters affect the time of mission completion when having different
number of quadcopters used in the simulation.
Future research should be done on how artificial intelligence can be used in the programing
of these quadcopters in order for collision between them to be limited such that the mobility
of these quadcopter is managed well.