The Autonomy Evolution in Unmanned Aerial Vehicle: Theory, Challenges and Techniques

Abstract

The research areas in the field of UAVs have increased considerably during the last years, the research in this field is driven by the specific needs of each organization that conduct the research, There are two main research areas, the first is the operational and it is conducted by the governmental institutions and the universities, and the second is the technological and it is conducted mainly by the companies, This paper discusses the current technological research topics in the field of UAVs, focusing on the fuzzy-logic based methods which are employed in many control problems to increase the level of autonomy, the fuzzy-logic is considered as a promising hot subject which contains many active research topics and multiple potential tools for solving complex control problems to extend the UAV capabilities to perform different functions like Optimal path planning, Collision avoidance, Trajectory motion and path following autonomously without the need of the human pilot with the minimum human supervision, the paper illustrates the different levels, functions and challenges of autonomy and a comparative analysis is conducted to analyze four potential directions which are considered to be promising areas for fuzzy-logic based approaches. It also highlights the two main areas of AI research in the field of UAV autonomous flight, 1) the imitation of the human pilot and 2) the high-level applications like image evaluation, and how to tackle some of the problems in these areas with aid of fuzzy-logic based machine learning algorithms.

Unmanned Aerial Vehicle Surveying and Mapping Trajectory Scheduling and Autonomous Control for Landslide Monitoring

“…With its high precision, high mobility, and high efficiency, it is suitable for operation in a variety of complex environments. [12][13][14][15].…”