Maze solving robot using image processing

Maze solving problem involves determining the path of a mobile robot from its initial position to its destination while traversing through environment consisting of obstacles. In addition, the robot must follow the best possible path among various possible paths present in the maze. Applications of such autonomous vehicles range from simple tasks like robots employed in industries to carry goods through factories, office buildings and other workspaces to dangerous or difficult to reach areas like bomb sniffing, finding humans in wreckage, etc. Existing robots employed in labyrinth problems use long process of training and are incapable of adjusting to dynamic environments. The method proposed here involves image processing and path finding algorithm; which works faster because of beforehand acquiring the maze's data rather than going through the maze cell by cell. The entire maze is captured to determine the possible paths and using Direction Envelope Algorithm for finding the best route. This approach gives robot a prognosis and avoids being trapped or falling in loops.