An Unveiling Navigation in Fog Ambiance by FPGA based Autonomous Vehicle with Minimal Sensing

This paper provides an approach for reference-less object detection for outdoor environment adaptable for navigating an autonomous vehicle. The computational efficiency of the image processing is to be questioned on its throughput in practical environment; a minimal sensing approach is needed to fulfil the gap formed due to this, so we propose a heuristic approach for tracking an object in dense fog ambiance. Driving through an environment with partial visibility may be fatal; a solution to this problem relies in prior intimation of object to be confronted based on the echo signal obtained. Depending on the nature of the obstacle, it can be dodged accordingly. As soon as the obstacle is detected the array of sensors gives the basic information of the obstacle. The Proposed algorithm is capable enough of finding the distance between the objects and analysing them through control unit designed by FPGA thereby confirming their nature of being static or dynamic. Efficiently making the robot to traverse through this adverse environment. This can be extended/applied to the field of automotive.