Publicação em atas de evento científico Q2
Using distance sensors to perform collision avoidance maneuvres on UAV applications
António Raimundo (Raimundo, A.); Diogo Peres (Peres, D.); Nuno Santos (Santos, N.); Pedro Sebastião (Sebastião, P.); Nuno Souto (Souto, N.);
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Ano (publicação definitiva)
2017
Língua
Inglês
País
Alemanha
Mais Informação
Web of Science®

N.º de citações: 0

(Última verificação: 2024-04-19 20:02)

Ver o registo na Web of Science®

Scopus

N.º de citações: 2

(Última verificação: 2024-04-16 09:11)

Ver o registo na Scopus


: 0.3
Google Scholar

N.º de citações: 10

(Última verificação: 2024-04-19 09:01)

Ver o registo no Google Scholar

Abstract/Resumo
The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. “Sense and Avoid” algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk’s flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G). Some tests were made in order to evaluate the “Sense and Avoid” algorithm’s overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and “Brake” mode on a real outdoor, proving its concepts.
Agradecimentos/Acknowledgements
--
Palavras-chave
UAV,Object collision avoidance,Distance sensing,LiDAR,3D environment,Drone,3D vehicle
  • Ciências da Computação e da Informação - Ciências Naturais
  • Outras Engenharias e Tecnologias - Engenharia e Tecnologia
  • Engenharia Eletrotécnica, Eletrónica e Informática - Engenharia e Tecnologia
  • Geografia Económica e Social - Ciências Sociais
Registos de financiamentos
Referência de financiamento Entidade Financiadora
UID/EEA/50008/2013 Fundação para a Ciência e a Tecnologia