Name
Abstract | ||
|---|---|---|
This paper presents a learning-based vehicle control system capable of navigating autonomously. Our approach is based on image processing, road and navigable area recognition, template matching classification for navigation control, and trajectory selection based on GPS waypoints. The vehicle follows a trajectory defined by GPS points avoiding obstacles using a single monocular camera and maintaining the vehicle in the road lane. Different parts of the image, obtained from the camera, are classified into navigable and non-navigable regions of the environment using neural networks. They provide steering and velocity control to the vehicle. Several experimental tests have been carried out under different environmental conditions to evaluate the proposed techniques. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.neucom.2012.07.040 | Neurocomputing |
Keywords | Field | DocType |
different part,navigable area recognition,vision-based waypoint,single monocular camera,image processing,velocity control,road lane,different environmental condition,gps waypoints,navigation control,artificial neural network,learning-based vehicle control system,compass,artificial neural networks,templates,computer vision | Template matching,Computer vision,Compass,Image processing,Waypoint,Global Positioning System,Artificial intelligence,Template,Artificial neural network,Mathematics,Trajectory | Journal |
Volume | ISSN | Citations |
107, | 0925-2312 | 5 |
PageRank | References | Authors |
0.65 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jefferson R. Souza | 1 | 46 | 7.19 |
| Gustavo Pessin | 2 | 164 | 23.10 |
| Patrick Yuri Shinzato | 3 | 59 | 4.98 |
| Fernando S. Osorio | 4 | 6 | 1.02 |
| Denis F. Wolf | 5 | 311 | 30.16 |