Advancing an engineering program with autonomous vehicles
Sacred Heart University is a private university in Connecticut with an academic program that emphasizes career-focused, project-based learning.
Dr. Tolga Kaya joined the engineering department to start a program that complements skills students learn in the computer and electrical engineering programs. Under his leadership, he integrated smart vehicles into the curriculum. The program started with drones and expanded to drones, ground robots, and aeros using the Quanser Autonomous Vehicles Research Studio. Now students in the engineering program are practicing SIMULINK and MatLab on the autonomous vehicles system, receiving control systems certifications, and publishing and presenting their research at international conferences.
Enhance the smart vehicles program with a reliable platform
Dr. Kaya started a smart vehicles program with drones to complement the university’s computer and electrical engineering programs. The program was starting to use MATLAB in multiple courses, and they wanted to explore that more. They were looking for a standard platform their students could practice on that they knew would work. They needed to decide if they should design their own platform or use an established one to practice MATLAB.
An autonomous vehicles research studio for teaching, certification, and research
“It was love at first sight,” thought Dr. Kaya when he came across the Quanser Autonomous Vehicles Research Studio. It was an established platform by Quanser, the leader in engineering lab equipment for teaching and research. His students could learn MATLAB and put it into practice with drones, ground robots, and aeros.
He partnered with Quanser and AET Labs to bring this research studio to their new lab at Sacred Heart University. The Quanser engineering team stepped in for troubleshooting and consultation when they started and participated in workshops providing control systems certifications.
Dr. Kaya’s team also leveraged Quanser’s online course material to create on-demand learning for students on the university’s Blackboard system.
Since implementing the research studio, students have published research papers and presented them at IEEE conferences.
The use of autonomous landing of aerial vehicles is increasing in demand. Applications of this ability can range from simple drone delivery to unmanned military missions. To be able to land at a spot identified by local information, such as a visual marker, creates and efficient and versatile solution. This allows for a more user/consumer friendly device overall. To achieve this goal the use of computer vision and an array of ranging sensors will be explored. In our approach we utilized an April Tag as our location identifier and point of reference. MATLAB/Simulink interface was used to develop the platform environment.
IEEE International Conference of Electro/Information Technology, 2021
G. Bitencourt, EJ. Brown, C. Bleimling, G. Lai, A. Molki, T. Kaya