Autonomous Navigation of Robots on Roads using Vision-Based Techniques for Road Identification and Lane Detection

Autonomous robot navigation on Indian roads presents unique challenges, particularly within campuses limited by weak GPS signals due to surrounding buildings and trees. This paper proposes a cost-effective solution for navigating such environments using a DC-powered robot vehicle within the campus of CDAC Mumbai. The approach leverages computer vision for lane detection and road demarcation, eliminating reliance on GPS. The lane detection approach utilises binary mask generation, edge detection, and Hough transform, while road demarcation employs colour filtering, contouring, and moments from the OpenCV library. Experimental results demonstrate a 72% navigation accuracy with minimal false detections. This algorithm is applicable for real-time scenarios, and enables autonomous vehicle navigation using minimal and cost-effective sensors, making it suitable for environments with obstructed GPS signals.