Moving target search is a challenging dynamic path planning problem. In this scenario,
unmanned aerial vehicles endeavor to locate a moving entity based on sensor information …

This paper presents a novel algorithm named the motion-encoded particle swarm
optimization (MPSO) for finding a moving target with unmanned aerial vehicles (UAVs) …

Effectively strategizing the trajectories of multiple Unmanned Aerial Vehicles (UAVs) within a
dynamic environment to optimize the search for and tracking of mobile targets presents a …

Unmanned aerial vehicles (UAVs) searching for a moving target is a complex search
optimization problem that aims to find a path with maximum probability of observing the …

Particle swarm optimization (PSO), one of the classical path planning algorithms, has been
considered for unmanned aerial vehicle (UAV) path planning more frequently in recent …

This study suggests an improved chaos sparrow search algorithm to overcome the problems
of slow convergence speed and trapping in local optima in UAV 3D complex environment …

Complete and efficient detection of unknown targets is the most popular application of UAV
swarms. Under most situations, targets have directional characteristics so that they can only …

In the Unmanned Aerial Vehicle (UAV) system, finding a flight planning path with low cost
and fast search speed is an important problem. However, in the complex three-dimensional …

In this paper, a new optimization algorithm called Motion-Encoded Genetic Algorithm with
Multiple Parents (MEGA-MPC) is developed to locate moving targets using multiple …

Automatic path planning problem is essential for efficient mission execution by unmanned
aerial vehicles (UAVs), which needs to access the optimal path rapidly in the complicated …