The majority of the research efforts that aim to solve UAV path optimization problems in a
Reinforcement Learning (RL) setting focus on closed spaces or urban areas as the …

We study the routing of Unmanned Aerial Vehicles (UAVs) in the presence of the risk of
enemy threats. The main goal is to find optimal routes that consider targets visited, threat …

This paper investigates an efficient algorithm for trajectory planning problem of autonomous
unmanned aerial vehicles which fly over three-dimensional terrains. The proposed algorithm …

We consider a type of routing problems common in defence and security, in which we
control a fleet of unmanned aerial vehicles (UAVs) that have to reach one or more target …

Tactical UAV path planning under radar threat using reinforcement learning involves
particular challenges ranging from modeling related difficulties to sparse feedback problem …

In some operations, military helicopters are required to hover or fly very low to ground to
avoid or minimise radar detection. Hence, during pre-flight planning, helicopters pilots need …

This research determines improved flight-path routes that make maximum utilization of
terrain-masking opportunities, and defending radar and missile system equipment …

This paper presents a UAV path planning approach to consider flight cost functions. The
UAV flight paths are generated using quintic Hermite interpolation. These paths are constant …

The practical applications of mobile robots are widely implemented in various areas, such as
education, industry, environment, and civil applications. The requirements of robots' …

Abstract The use of Unmanned Aerial Vehicles (UAVs) and the importance of its role have
evolved and increased recently in both civilian and military operations. In this research, we …