Date of Award
Spring 5-2025
Document Type
Thesis
Department
Electrical Engineering and Computer Science
First Advisor
Dr. Tom Springer
Second Advisor
Dr. Trudi Qi
Third Advisor
Dr. Peiyi Zhao
Abstract
Common robotic navigation techniques often utilize GPS to set up the robot’s reference frame, which is not possible in environments, such as indoor facilities, underground passages, and disaster zones, where GPS is not available. This research explores the integration of a Boston Dynamics Spot robot with a Tello drone to form a non-GPS-based autonomous navigation system. By leveraging coordinate transformation logic, this study enables real-time aerial reconnaissance and ground-based waypoint navigation without reliance on GPS. The methodology includes software development using the Spot SDK and Tello APIs, a virtual networked solution for integration, and an experimental setup to validate navigation accuracy. The integration showcases the feasibility of multi-agent robotic collaboration in constrained environments, contributing toward advancements in autonomous exploration and search-and-rescue systems.
DOI
10.36837/chapman.000643
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
R. L. Alexander, III, "Autonomous search and rescue: Real-time drone and robotic dog integration," M. S. thesis, Chapman University, Orange, CA, 2025. https://doi.org/10.36837/chapman.000643
