Design, development and guidance of the Airborne’s quadrotor

Strano, Bruno (2022) Design, development and guidance of the Airborne’s quadrotor, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria biomedica, elettrica e dei sistemi, 34 Ciclo. DOI 10.48676/unibo/amsdottorato/10221.
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Abstract

The main goal of the Airborne project is to develop, at technology readiness level 8 (TRL8), a few selected robotic aerial technologies for quick localization of victims by avalanches by equipping drones with two forefront sensors used in SAR operations in case of avalanches, namely the ARVA and RECCO. This thesis focuses on the design, development, and guidance of the TRL8 quadrotor developed during the project. We present and describe the design method that allowed us to obtain an EMI shielded UAV capable of integrating both RECCO and ARVA sensors. Besides, is presented the avionics and power train design and building procedure in order to obtain a modular UAV frame that can be easily carried by rescuers and achieves all the performance benchmarks of the project. Additionally, in addition to the onboard algorithms, a multivariate regressive convolutional neural network whose goal is the localization of the ARVA signal is presented. On guidance, the automatic flight procedure is described, and the onboard waypoint generator algorithm is presented. The goal of this algorithm is the generation and execution of an automatic grid pattern without the need to know the map in advance and without the support of a control ground station (CGS). Moreover, we present an iterative trajectory planner that does not need pre-knowledge of the map and uses Bézier curves to address optimal, dynamically feasible, safe, and re-plannable trajectories. The goal is to develop a method that allows local and fast replannings in case of an obstacle pop up or if some waypoints change. This makes the novel planner suitable to be applied in SAR operations. The introduction of the final version of the quadrotor is supported by internal flight tests and field tests performed in real operative scenarios by the Club Alpino Italiano (CAI).

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Strano, Bruno
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
34
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
UAV, SAR, EMI, ARVA, RECCO, path planning, signal recognition
URN:NBN
DOI
10.48676/unibo/amsdottorato/10221
Data di discussione
22 Giugno 2022
URI

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