Enhancing Assault Maneuvers in Simulated Scenarios of Multiple Invader Kamikaze Drones through the Utilization of a Modified Adaptive Elforce Algorithm
Abstract
The development of autonomous drone technology has led in their widespread deployment,
especially in combat scenarios. One instance of this is the utilization of kamikaze drones, as
seen in the Ukraine war. Autonomous defense drones have been used to counter these
invading kamikaze drones. This study focuses on simulating scenarios involving invader vs.
defender drones, primarily exploring invader drone maneuver motions to maximize damage
inflicted on chosen targets. The work we conducted presents an enhanced el-force algorithm
that employs Coulomb's Law-based maneuver techniques to improve the effectiveness of
multiple kamikaze invader drones when engaging target defended by defender drones. We
aim to improve traditional el-force by addressing key challenges such as siege tendencies and
unproductive conduct. In addition, we explore various attacking formations to determine the
most effective formation. To evaluate the performance of our proposed algorithm, we
conducted simulation in a dynamic 3D environment, employing damage inflicted as the
evaluation metric. Through rigorous testing, we conclusively demonstrate that our proposed
method combining with a circular formation, outperforms alternative attacking maneuvers
and formations. Our findings provide insights into optimal maneuver movements and
attacking formations, improving the effectiveness of invader drones in engaging and
damaging designated targets.
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