Authors:

Natasha Gundapaneni

Date Created:

Not specified

Course Title:

Professor:

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About Paper:

Our research focuses on the autonomous navigation of Unmanned Aerial Vehicles (UAVs) or drones within maze-like structures, with an emphasis on speed and efficiency. Using advanced mapping software and sensors, we construct accurate representations of these structures and identify the most optimal paths through path-planning algorithms. Our study utilizes a Docker environment that integrates ROS2, Gazebo Garden, and a PX4 simulator for drone operations. The methodology involves a two-stage testing process: we initially validate path efficiency through simulated tests, then proceed to real-world trials with UAVs, taking into account factors such as air resistance and hardware constraints. These insights not only make significant contributions to our understanding of autonomous UAV navigation but also set the stage for potential applications in sectors such as agriculture and defense, marking an important advancement in the evolution of autonomous UAV technology.

Source:

Purdue University / 2023

Topics:

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Co-authors:

Natasha Gundapaneni