Modeling and characterization of an educational bench test for aerial angular control of multirotors in partnership with Eidgenössische Technische Hochschule Zürich (ETHZ)

• Grant number: 25/06912-9
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: June 20, 2025
• End date: October 19, 2025
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: André Carmona Hernandes
• Grantee: Guilherme Barros Villela
• Supervisor: Stefano Mintchev
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Institution abroad: Swiss Federal Institute of Technology Zurich, Switzerland
• Associated to the scholarship: 23/11661-0 - Modeling and characterization of an educational bench test for aerial angular control of multirotors, BP.IC

Abstract

Morphing drones, featuring adaptive physical structures inspired by biologicalsystems, represent a significant advancement in unmanned aerial systems (UAS).These drones enhance agility, energy efficiency, and performance by dynamicallyadjusting their morphology to meet environmental challenges. Applications spanenvironmental monitoring, disaster response, and precision agriculture, where theiradaptability and operational efficiency provide distinct advantages. Advanced controltechniques, including System Identification (SysId), Model Predictive Control (MPC),and Reinforcement Learning (RL), have further empowered drones to navigatecomplex and dynamic scenarios. Morphological drones excel in real-world taskssuch as biodiversity monitoring, with studies demonstrating their ability to adjustparameters like inertia and center of gravity for improved navigation and stability.Simulation platforms, such as OmniDrones and Aerial Gym, play a criticalrole in advancing RL-based control systems, offering high-fidelity, GPU-acceleratedenvironments for large-scale policy training. Complemented by hardware-in-the-loop(HIL) and field testing, these methodologies ensure robust system development.This research project focuses on:9i) simulating soft drones integrating frames withnonlinear elastic properties, and (ii) explore RL control policies to achieve agileflight behaviors. By uniting adaptive morphology, advanced control methods, andcutting-edge simulation tools, this work contributes to the development of highlyversatile and capable aerial robotics systems.