This review article offers an in-depth analysis of cooperative motion planning and control in
aerial-ground autonomous systems, emphasizing their methods and applications. It explores …

Drones have recently become one of the most important technological breakthroughs. They
have opened the horizon for a vast array of applications and paved the way for a diversity of …

Path planning is one of the most important steps in the navigation and control of Unmanned
Aerial Vehicles (UAVs). It ensures an optimal and collision-free path between two locations …

Unmanned aerial vehicles (UAVs) have recently attracted the attention of researchers due to
their numerous potential civilian applications. However, current robot navigation …

Unmanned air vehicles operate in highly dynamic and unknown environments where they
can encounter unexpected and unseen failures. In the presence of emergencies …

This paper presents a hybrid differential evolution (DE) with quantum-behaved particle
swarm optimization (QPSO) for the unmanned aerial vehicle (UAV) route planning on the …

A new variant of particle swarm optimization (PSO), named phase angle-encoded and
quantum-behaved particle swarm optimization (θ-QPSO), is proposed. Six versions of θ …

To date, a large number of optimization algorithms have been presented for Autonomous
Underwater Vehicle (AUV) path planning. However, little effort has been devoted to compare …

We proposed a new learning algorithm, named Geometric Reinforcement Learning (GRL),
for path planning of Unmanned Aerial Vehicles (UAVs). The contributions of GRL are as:(1) …

Based on a bio-heuristic algorithm, this paper proposes a novel path planner called obstacle
avoidance beetle antennae search (OABAS) algorithm, which is applied to the global path …