There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones,
in different applications such as packages delivery, traffic monitoring, search and rescue …

It is a long-term challenging task to develop an intelligent agent that is able to navigate in 3D
environment using only visual input in an end-to-end manner. In this paper, we introduce a …

摘要深度强化学习算法在实现无人机(unmannedaerialvehicle, UAV) 导航任务的应用越来越
广泛. 然而, 利用融合先验策略的训练过程中, 由于其占比线性衰减, 导致模型训练速度缓慢 …

Purpose: Real-life applications using quadrotors introduce a number of disturbances and
time-varying properties that pose a challenge to flight controllers. We observed that, when a …

In this paper, we develop a method for deep reinforcement of training simulation for
Quadcopter and perform a comparison in the training of the neural network on x86 based …

The existing deep reinforced learning algorithms cannot see local environments and have
insufficient perceptual information on UAV autonomous navigation tasks. The paper …

The United States Air Force Test Pilot School (USAF TPS), in partnership with Lockheed
Martin Skunk Works, developed and tested a suite of algorithms and artificial intelligence …

Reinforcement Learning for Quadrotor Trajectory Control in Virtual Environments. Rio de
Janeiro, 2021. 118p. Dissertação de Mestrado–Departamento de Engenharia Elétrica …