An autonomous path finding robot using Q-learning

The main objective of this paper is to develop an autonomous robot that show the use of Q-learning for navigation in a complete unknown environment. This will calculate the shortest path from current state to goal state by analyzing the environment through captured images. Further the captured images will be processed through image processing and machine learning techniques. The proposed method also takes care of the obstacles present in that environment. Initially, the unknown environment will be captured using a camera. Obstacle detection method will be applied on it. Then the grid based map obtained from vision based obstacle detection method will be given to Q-Learning algorithm which will be further made live with motion planning.