Honors Theses
Advisor
Krishna Bhavithavya Kidambi, Ph.D.
Department
Mechanical and Aerospace Engineering
Publication Date
4-23-2025
Document Type
Honors Thesis
Abstract
In the evolving landscape of unmanned aerial vehicles (UAVs), the autonomy and stability of quadrotors are crucial, especially in critical applications such as search and rescue missions and surveillance. This research focuses on the development and implementation of planning and control algorithms within the Robot Operating System (ROS2) framework. Initial work focused on developing Proportional-Integral- Derivative (PID) control algorithm in a realistic simulated environmental condition, incorporating the effects of sensor noise. Following successful simulations, the study transitioned to real-world testing, validating the effectiveness of the proposed solutions in ROS2. The work conducted has not only demonstrated the practical utility of these algorithms in both simulated and real-world environments but has also laid the groundwork for more advanced applications in aerial robotics. The successful integration of ROS2 has opened up new avenues for modularity and scalability, critical for the ongoing evolution of autonomous drone technology.
Permission Statement
This item is protected by copyright law (Title 17, U.S. Code) and may only be used for noncommercial, educational, and scholarly purposes.
Keywords
Undergraduate research
eCommons Citation
Johnston, Kevin P., "Enhancing Quadrotor Autonomy Using Robust Control Algorithms" (2025). Honors Theses. 475.
https://ecommons.udayton.edu/uhp_theses/475
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