An image matching system for autonomous UAV navigation based on neural network
- Resource Type
- Conference
- Authors
- Braga, Jose R. G.; Velho, Haroldo F. C.; Conte, Gianpaolo; Doherty, Patrick; Shiguemori, Elcio H.
- Source
- 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV) Control, Automation, Robotics and Vision (ICARCV), 2016 14th International Conference on. :1-6 Nov, 2016
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Image edge detection
Correlation
Image matching
Neurons
Global Positioning System
Unmanned aerial vehicles
Training
- Language
This paper proposes an image matching system using aerial images, captured in flight time, and aerial geo-referenced images to estimate the Unmanned Aerial Vehicle (UAV) position in a situation of Global Navigation Satellite System (GNSS) failure. The image matching system is based on edge detection in the aerial and geo-referenced image and posterior automatic image registration of these edge-images (position estimation of UAV). The edge detection process is performed by an Artificial Neural Network (ANN), with an optimal architecture. A comparison with Sobel and Canny edge extraction filters is also provided. The automatic image registration is obtained by a cross-correlation process. The ANN optimal architecture is set by the Multiple Particle Collision Algorithm (MPCA). The image matching system was implemented in a low cost/consumption portable computer. The image matching system has been tested on real flight-test data and encouraging results have been obtained. Results using real flight-test data will be presented.