Authors:

Taeha Jeong

Date Created:

Not specified

Course Title:

Professor:

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About Paper:

The demand for Unmanned Aerial Vehicles (UAV), commonly known as drones, is exponentially growing worldwide. These machines find utility across diverse sectors, including inspection, monitoring, exploration, product delivery, and military operations. While drones can offer immense potential to benefit humanity, there are challenges that require attention. One significant issue is stabilizing drones in the presence of wind turbulence. As these are unmanned vehicles, the presence of automatic stabilization system is required of them. Previous research has focused on modeling and simulation realistic turbulence data and optimizing travel plans under windy conditions. Building upon the work, this study focused on further improving the existing model by attaching a cargo to the drone. Software tools such as PX4 Autopilot, Gazebo, Robot Operating System (ROS), and Python were used to retrieve, incorporate real-world wind data, and to model a cargo carrying drone. This study extends the previous drone stabilization model to accommodate the additional weight connected to it, impacting the aerodynamics and decision-making processes. Python and other software tools to were used to develop and evaluate a reinforcement model based on drone output and to load the trained model onto the drone for refinement and assessments. Future research will involve modeling different cargo shapes and weights to simulate more realistic environments. Keywords: UAV; AI; Simulation; Stabilization; Cargo

Source:

Purdue University / 2024

Topics:

No topics listed

Co-authors:

Taeha Jeong