Enhancing Quadrotor Autonomy using ROS-based Control Algorithms

Enhancing Quadrotor Autonomy using ROS-based Control Algorithms

Presenter(s)

Kevin Johnston

Comments

10:00-10:20, Kennedy Union 310

Description

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 algorithms in realistic simulated environmental conditions, 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.

Publication Date

4-23-2025

Project Designation

Honors Thesis

Primary Advisor

Krishna B. Kidambi

Primary Advisor's Department

Mechanical and Aerospace Engineering

Keywords

Stander Symposium, School of Engineering

Enhancing Quadrotor Autonomy using ROS-based Control Algorithms

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