Honors Theses
Date of Award
Spring 5-10-2025
Document Type
Undergraduate Thesis
Department
Computer and Information Science
First Advisor
Charles Walter
Second Advisor
Timothy Holston
Third Advisor
Byunghyun Jang
Relational Format
Dissertation/Thesis
Abstract
Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), when coordinated effectively, offer substantial potential for automating large-scale tasks—from search and rescue operations to precision agriculture. However, synchronizing these autonomous systems remains challenging, especially in time-sensitive missions requiring precision. This thesis investigates the design and algorithmic coordination of autonomous UAVs and UGVs, examining both single-vehicle scenarios and multi-agent (swarming) approaches. Using the Robot Operating System (ROS) as a communication backbone, I integrate GPS positioning with computer vision techniques through OpenCV, enabling accurate localization and object detection. During the development phase, I validate my methods using ArduPilot Software-in-the-Loop (SITL) simulations within Gazebo for both individual and swarm-based scenarios. Subsequently, by comparing three existing flight-planning algorithms and evaluating their integration with precision landing techniques, I identify the most efficient algorithm considering the project requirements. Finally, I test and validate this coordination framework through simulations that confirm reliable flight trajectories, payload delivery accuracy, and precise landings within the specified time constraints, culminating in successful real-world ongoing experiments.
Recommended Citation
Dhakal, Aashish, "Algorithms & Design Behind Autonomous UAVs and UGVs Coordinated System" (2025). Honors Theses. 3323.
https://egrove.olemiss.edu/hon_thesis/3323
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Included in
Digital Communications and Networking Commons, Navigation, Guidance, Control, and Dynamics Commons, Other Computer Engineering Commons, Robotics Commons
Comments
This research project was developed in preparation for the Raytheon Autonomous Vehicle Competition, which required fully autonomous UAV–UGV coordination for payload delivery. The system integrates open-source tools such as ROS, ArduPilot, and OpenCV with GPS and computer vision. Key hardware includes Pixhawk 6C controllers, RFD900X telemetry radios, and Here4 RTK GNSS modules, with onboard computation handled by Raspberry Pi. The system has been thoroughly tested and verified through both Gazebo-based ArduPilot SITL simulations and real-world field trials.