This is an Autonomous Survillance Robot Project
The autonomous robot is equipped with Arduino board that further has H-Bridge to control the motion of the robot, incremental encoders that are used to maintain the speed and keep track of the positioning, mostly used in feedback applications. And also, integrated with Ultrasonic Range Finder sensors in Arduino board that provide the feedback to the robot so that it can navigate through the fields and keep itself on the path
In this project, I have used Machine Learning Technique to detect Canola Leaves. This system is detecting canola leaves instead of weeds because there are hundreds of different types of weeds found in canola so instead of training the system to detect all sorts of weeds, it was decided to detect canola leaves and then apply the inverse logic to ignore the canola leaves and save the images of weeds with their location so that when the farmer is viewing these images he will be able to identify them himself and because of this system he will know the location of the weeds. This system will be mounted on an autonomous robot which will be able to navigate through canola fields
