Abstract
Simulation tools are often used in robotics education to transfer theoretical knowledge into practical experience. The correlation between practical and real-world experience depends on the quality of the simulation environment and its ability to serve as a replacement for the real world. In this study an environment for UAV education is proposed, where the transfer of theoretical knowledge into practical experience is achieved through the implementation of both simulation and real UAV deployment. Initially, this environment allows students to develop their applications in the simulation. Subsequently, in the later stages, they are able to easily deploy them into the educational UAV and test the solution in the drone laboratory. Compatibility between simulation and physical UAV is achieved by combining the appropriate components in both the simulation and physical UAV. The software technologies used include ROS, ArduPilot, and MavLink, while the hardware platform for the educational UAV was chosen as DroneCore.Suite by Airvolute s.r.o. These technologies are not only suitable for the proposed environment but are also commonly used across the robotics field, which enhances relevant students competencies. Later in the article, an example assignment is presented and described how to use the environment for UAV education in a classroom setting.
This article was written thanks to the generous support under the Operational Program Integrated Infrastructure for the project: “Research and development of the applicability of autonomous flying vehicles in the fight against the pandemic caused by COVID-19”, Project no. 313011ATR9, co-financed by the European Regional Development Fund. This publication was also supported by the project APVV-21-0352—“A navigation stack for autonomous drones in an industrial environment” and by the company Airvolute s.r.o.
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Sedláček, M., Mráz, E., Rajchl, M., Rodina, J. (2023). Environment for UAV Education. In: Balogh, R., Obdržálek, D., Christoforou, E. (eds) Robotics in Education. RiE 2023. Lecture Notes in Networks and Systems, vol 747. Springer, Cham. https://doi.org/10.1007/978-3-031-38454-7_22
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DOI: https://doi.org/10.1007/978-3-031-38454-7_22
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