Autonomous Navigation and Control Systems for Unmanned Aerial Vehicles in Complex Environments

Unmanned Aerial Vehicles (UAVs) have remained among the most modern equipment in many areas such as military, agriculture, and environmental fields by improving the aerial reconnaissance and data gathering. Some of the main concerns addressed in this paper are on UAV functioning where for instance, the identification of the barriers, the path to be followed and system stability. We also introduced and evaluate the current strategies of autonomous navigation as well as control to increase the response in the unpredictable scenarios. Our concept also embodies the new algorithms for successful avoidance of obstacles, the new methods of path planning, and new control structures realized with the help of the real-time operating systems, the language Python and C++. The findings of the proposed method in the controlled and complex cases illustrate the enhancement of navigation precision with an average error of 0. 200 meters of test track and operational at 10 meters in cluttered environments. Besides, response has been done faster and quicker as the average latency to any of the conventional techniques has been cut down to 20 milliseconds. When comparing to other known methods, the present proposed system is more accurate and prompter in its methodology. We think that such improvements increase several operations of UAVs in various fields including search and rescue, monitoring and surveillance, and environmental protection and guide future research themes such as real-life application of UAVs, sensor integration, and increasing the computational complexity of the algorithms. Therefore, the present work is useful for the field since it includes the problem solutions concerning the management and control of UAVs in the environment.