Comparing YOLOv3, YOLOv4 and YOLOv5 for Autonomous Landing Spot Detection in Faulty UAVs
Southern Illinois University Carbondale
Abstract
In-flight system failure is one of the major safety concerns in the operation of unmanned aerial vehicles (UAVs) in urban environments. To address this concern, a safety framework consisting of following three main tasks can be utilized: (1) Monitoring health of the UAV and detecting failures, (2) Finding potential safe landing spots in case a critical failure is detected in step 1, and (3) Steering the UAV to a safe landing spot found in step 2. In this paper, we specifically look at the second task, where we investigate the feasibility of utilizing object detection methods to spot safe landing spots in case the UAV suffers an in-flight failure. Particularly, we investigate different versions of the YOLO…
Citation impact
- FWCI
- 229.70
- Percentile
- 100%
- References
- 30
Authors
2- UNUpesh Nepal
Southern Illinois University Carbondale
- HEHossein EslamiatCorresponding
Southern Illinois University Carbondale
Topics & keywords
- Object detection
- Aerial image
- Plan (archaeology)
- Flight plan
- Object (grammar)