Modular Reinforcement Learning for Autonomous UAV Flight Control

Abstract

Recently, research on unmanned aerial vehicles (UAVs) has increased significantly. UAVs do not require pilots for operation, and UAVs must possess autonomous flight capabilities to ensure that they can be controlled without a human pilot on the ground. Previous studies have mainly focused on rule-based methods, which require specialized personnel to create rules. Reinforcement learning has been applied to research on UAV autonomous flight; however, it does not include six-degree-of-freedom (6-DOF) environments and lacks realistic application, resulting in difficulties in performing complex tasks. This study proposes a method of efficient learning by connecting two different maneuvering methods using modular learning for autonomous UAV flights. The proposed method divides complex tasks into simpler tasks, learns them individually, and then connects them in order to achieve faster learning by transferring information from one module to another. Additionally, the curriculum learning concept was applied, and the difficulty level of individual tasks was gradually increased, which strengthened the learning stability. In conclusion, modular learning and curriculum learning methods were used to demonstrate that UAVs can effectively perform complex tasks in a realistic, 6-DOF environment.

Delay-D: Research on the Lifespan and Performance of Storage Devices in Unmanned Aerial Vehicles

“…The technology of UAVs has been evolving and growing rapidly in recent years [1][2][3]. In particular, many UAV platforms have been proposed and evaluated, carrying various sensor devices, such as cameras, LIDAR, thermals, etc., in terms of practical flight [1,18].…”

“…The technology of UAVs has been evolving and growing rapidly in recent years [1][2][3]. In particular, many UAV platforms have been proposed and evaluated, carrying various sensor devices, such as cameras, LIDAR, thermals, etc., in terms of practical flight [1,18]. In various UAV platforms and systems, the storage device is a crucial component because a UAV must record onboard flight logs that include valuable information during flights (e.g., collected sensor values, commands, and signals) [19].…”

“…UAVs are evolving rapidly due to their diverse applications and advancements in technology. Therefore, numerous previous studies and commercial products have been designed for UAVs in recent years [1][2][3][4][5]23]. For example, Lee et al introduced the portability issues of tightly coupled software on UAVs and proposed a new software structure for UAV flight control software [23].…”

“…Unmanned aerial vehicles (UAVs) are rapidly evolving due to the demand spike in various industries, such as national defense, disaster management, and agriculture [1][2][3]. Recent advances in hardware technologies of UAVs, such as cameras, GPS, telemetry, storage, and sensor modules, significantly accelerate their widespread deployment.…”