Today, the development of unmanned aerial vehicles (UAVs) has attracted significant
attention in both civil and military fields due to their flight flexibility in complex and dangerous …

Featured Application The application of “Autonomous Navigation of Robots: Optimization
with DQN” involves using reinforcement learning techniques to optimize the navigation of …

Recently, autonomous driving has become one of the most popular topics for smart vehicles.
However, traditional control strategies are mostly rule-based, which have poor adaptability …

Motion capture systems are crucial in developing multi-quadrotor systems due to their ability
to provide fast and accurate ground truth measurements for tracking and control. This paper …

In this paper, we propose a C51-Duel-IP (C51 Dueling DQN with Independent Policy)
dynamic destination path-planning algorithm to solve the problem of autonomous navigation …

Advanced Driver Assistance Systems (ADAS) are only applied to relatively simple scenarios,
such as highways. If there is an emergency while driving, the driver should take control of …

Unmanned Aerial Vehicles (UAVs) are recognized as very useful tools to replace, help, or
assist humans in various missions, such as inspection and monitoring, surveillance, search …

摘要人工智能赋能下的无人机(unmanned aerial vehicles, UAV) 将推动未来战争向着无人化,
智能化趋势发展, 自主化的感知, 判断, 决策, 行动的作战单元或群体, 具备颠覆战争规则 …

In this paper, a novel reward-based learning method is proposed for unmanned aerial
vehicles to achieve multiobstacle avoidance. The Markov jump model was first formulated …

In agriculture, irrigation is essential for providing water to crops based on the type of soil they
are grown in. To achieve success in farming, it is important to evaluate soil fertility …