Recognizing Human Actions: A Deep Learning Model for UAV Piloting - Cabral, Iohana A. Torres; Wehrmeister, Marco Aurelio; Lazzaretti, André Eugenio; Lopes, Heitor Silverio (Anais do Simpósio Brasileiro de Robótica e Simpósio Latino Americano de Robótica (SBR/LARS); 2024: Anais do XVI Simpósio Brasileiro de Robótica e XV Workshop de Robótica na Educação, 2024)
This project aims to explore action recognition through a deep learning model generated by Convolutional Neural Networks, establishing the foundation for human-robot interaction in a scenario where Unmanned Aerial Vehicles (UAV) are controlled exclusively by visual commands. The model analyzes images captured by an onboard camera using and classifies them into nine categories. Each category issues a specific command based on human actions performed by individuals properly equipped with personal protective equipment. The results demonstrate the feasibility of the proposed approach, opening room for improvements aiming its use in more complex scenarios.