In this paper a vision-based approach for guidance and safe landing of an Unmanned Aerial Vehicle (UAV) is proposed. The UAV is required to navigate from an initial to a final position in a partially known environment. The guidance system allows a remote user to define target areas from a high resolution aerial or satellite image to determine either the waypoints of the navigation trajectory or the landing area. A feature-based image-matching algorithm finds the natural landmarks and gives feedbacks to an onboard, hierarchical, behaviour-based control system for autonomous navigation and landing. Two algorithms for safe landing area detection are also proposed, based on a feature optical flow analysis. The main novelty is in the vision-based architecture, extensively tested on a helicopter, which, in particular, does not require any artificial landmark (e.g., helipad). Results show the appropriateness of the vision-based approach, which is robust to occlusions and light variations.
A Vision-based guidance system for UAV navigation and safe landing using natural landmarks / Cesetti, A.; Frontoni, Emanuele; Mancini, Adriano; Zingaretti, Primo; Longhi, Sauro. - In: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS. - ISSN 0921-0296. - 57(1-4):(2010), pp. 233-257. [10.1007/s10846-009-9373-3]
A Vision-based guidance system for UAV navigation and safe landing using natural landmarks
FRONTONI, EMANUELE;MANCINI, ADRIANO;ZINGARETTI, PRIMO;LONGHI, SAURO
2010-01-01
Abstract
In this paper a vision-based approach for guidance and safe landing of an Unmanned Aerial Vehicle (UAV) is proposed. The UAV is required to navigate from an initial to a final position in a partially known environment. The guidance system allows a remote user to define target areas from a high resolution aerial or satellite image to determine either the waypoints of the navigation trajectory or the landing area. A feature-based image-matching algorithm finds the natural landmarks and gives feedbacks to an onboard, hierarchical, behaviour-based control system for autonomous navigation and landing. Two algorithms for safe landing area detection are also proposed, based on a feature optical flow analysis. The main novelty is in the vision-based architecture, extensively tested on a helicopter, which, in particular, does not require any artificial landmark (e.g., helipad). Results show the appropriateness of the vision-based approach, which is robust to occlusions and light variations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.