UAV Obstacle Avoidance Algorithm to Navigate in Dynamic Building Environments

In this work, a real-time collision avoidance algorithm was presented for autonomous navigation in the presence of fixed and moving obstacles in building environments. The current implementation is designed for autonomous navigation between waypoints of a predefined flight trajectory that would be p...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Drones (Basel) Ročník 6; číslo 1; s. 16
Hlavní autoři: Aldao, Enrique, González-deSantos, Luis, Michinel, Humberto, González-Jorge, Higinio
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.01.2022
Témata:
Aircraft
Algorithms
Autonomous navigation
Civil engineering
Cloud computing
Collision avoidance
Construction
Control theory
Critical path
Drones
LiDAR
Linear programming
Maneuvers
Moving obstacles
Neural networks
non-linear programming
Obstacle avoidance
Optimization
Real time
Remote sensing
Scanners
Sensors
Three dimensional models
UAVs in construction
Unmanned aerial vehicles
Vehicles
Waypoints
ISSN:2504-446X, 2504-446X
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this work, a real-time collision avoidance algorithm was presented for autonomous navigation in the presence of fixed and moving obstacles in building environments. The current implementation is designed for autonomous navigation between waypoints of a predefined flight trajectory that would be performed by an UAV during tasks such as inspections or construction progress monitoring. It uses a simplified geometry generated from a point cloud of the scenario. In addition, it also employs information from 3D sensors to detect and position obstacles such as people or other UAVs, which are not registered in the original cloud. If an obstacle is detected, the algorithm estimates its motion and computes an evasion path considering the geometry of the environment. The method has been successfully tested in different scenarios, offering robust results in all avoidance maneuvers. Execution times were measured, demonstrating that the algorithm is computationally feasible to be implemented onboard an UAV.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2504-446X
2504-446X
DOI:10.3390/drones6010016