Problem-Based Learning: A Study on Drone Trajectory Planning for Medical Logistics

• André Palharini Nascimento dos Santos UFSM
• Gabriel Ramires Berle IFRS
• Fernanda Pinto Mota IFRS
• Leonardo Martins Brisolla UFSM
• Daniel Fernando Tello Gamarra UFSM
• Anselmo Rafael Cukla UFSM

Resumo

The shortage of blood in hospital stocks is a critical challenge for the Brazilian healthcare system, especially during emergencies. In this context, the use of drones for blood transportation emerges as a promising alternative, capable of reducing response times and optimizing routes in both urban and remote regions. This paper presents a case study involving Engineering and Computer Science students from public institutions in southern Brazil, using a Problem-Based Learning (PBL) approach. Students were challenged to plan drone trajectories through manual calculations and computer simulations. The results allowed for a comparative analysis of accuracy between the methods and highlighted the pedagogical potential of emerging technologies in training professionals capable of addressing the challenges of medical logistics. The findings also demonstrate the technical and educational feasibility of using drones in the transportation of blood products.

Palavras-chave: Trajectory planning, Computational modeling, Transportation, Manuals, Robot sensing systems, Data models, Numerical models, Blood, Drones, Logistics, Problem-Based Learning (PBL), Drone Trajec-tory Planning, Medical Logistics, Blood Transportation, Simulation, Engineering Education, Emerging Technologies, UAV