Abstract
In this paper, we have designed a autonomous vehicle which is cost effective and powered by Robotic Operating System (ROS). The vehicle is capable of maintaining a constant speed and distance for monitoring or surveillance. ROS is implemented for trajectory tracking and telemetry. A low cost compact on-board embedded system powers the vehicle. Various image processing techniques are been implemented for navigation and obstacle detection. Artificial Neural Network which helps in finding the shortest path by using the acquired data from image processing. Different controllers were implemented for movement and obstacle avoidance including PI and PID. The performance were compared and the results are also discussed in this paper.
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