Abstract:
In computer vision the technique when information is obtained from the devices or sensors and then those information is used to make a map or store the information in a map is known as simultaneous localization and mapping (SLAM). This research study presents an analysis of feature point detection and mapping for agricultural environments. I perform feature point map building using the front-facing camera and the bottom-facing camera of an airborne quad copter. The SLAM technique that I use to detect feature points and build a map is achieved by a single monocular camera. These SLAM techniques gives us the position of the camera trajectory estimates as well as the positions of the feature points estimates it detects. In the future, these techniques could be used for autonomous navigation of an airborne quad copter in agricultural environments.
