Authors: Dr. Prakash P, Kannagi L, Aakash K, Amizhdhan L, Pragathesh Kumar
Abstract: The intelligent autonomous vehicle utilizing GPS and camera technology has been programmed to avoid obstacles in its environment. Unlike normal vehicles, this car combines computer vision features with GPS technology. The technology helps the car recognize obstacles and make evasive maneuvers in real-time. A camera is fixed on the car's chassis, and it is constantly recording the environment around it. The video frames are then analyzed using machine learning techniques to detect obstructions like walls, cars, pedestrians as well as anything else that may prevent the car from moving. The car is able to gather accurate visual information which helps it identify the obstacles shape, size, and position. In addition, the automobile contains a GPS module that provides adequate positioning to pinpoint the exact location of the car. The GPS module picks up signals from satellites to ascertain the car's current position with a high degree of accuracy. Likewise, the car also uses a decision-making algorithm that takes into consideration visual data from the camera, GPS data, and predefined permissible routes. The algorithm processes the relevant data and helps the system determine the most optimal route while avoiding obstacles. When an obstacle is detected in its path, the car automatically alters its trajectory to avoid the obstacle while maintaining its intended route. In summary, the obstacle-avoiding car that utilizes a camera and GPS module offers a promising approach to autonomous navigation [1]. By integrating computer vision methods with GPS positioning, the car can sense and react to its surroundings, ensuring safe and efficient travel in complex and ever-changing environments.
DOI: http://doi.org/10.5281/zenodo.16606351
