Path planning is one of the key technologies for autonomous flight of Unmanned Aerial
Vehicle. Traditional path planning algorithms have some limitations and deficiencies in the …

Autonomous navigation in unknown environment is still a hard problem for small Unmanned
Aerial Vehicles (UAVs). Recently, some neural network-based methods are proposed to …

The unmanned aerial vehicles (UAVs) are competent to perform a variety of applications,
possessing great potential and promise. The deep neural networks (DNN) technology has …

Unmanned aerial vehicles (UAVs) are important in reconnaissance missions because of
their flexibility and convenience. Vitally, UAVs are capable of autonomous navigation, which …

Path planning is one of the most essential part in autonomous navigation. Most existing
works suppose that the environment is static and fixed. However, path planning is widely …

Path planning algorithms are of paramount importance in guidance and collision systems to
provide trustworthiness and safety for operations of autonomous unmanned aerial vehicles …

Path planning remains a challenge for Unmanned Aerial Vehicles (UAVs) in dynamic
environments with potential threats. In this paper, we have proposed a Deep Reinforcement …

Path planning for unmanned aerial vehicles (UAVs) has been widely considered in various
tasks. Existing path planning algorithms, such as A* and Jump Point Search, have been …

Real-time path planning is crucial for intelligent vehicles to achieve autonomous navigation.
In this paper, we propose a novel deep neural network (DNN) based method for real-time …

Unmanned Aerial vehicles (UAVs) are widely used as network processors in mobile
networks, but more recently, UAVs have been used in Mobile Edge Computing as mobile …