Publication

Abstract : In recent times, automation has achieved improvements by quality, accuracy, and precision. We introduce SAM-Sensible Autonomous Machine, performing two operations. Interfacing SAM to follow back an object by crossing obstacles and to reach the destination by sensing the response signal from Smartphone through Reinforcement Learning. Monitoring entire surrounding using Recurrent Convolutional Neural Networks Algorithm to identify the colour patterns of traffic signal by processing images through TensorFlow and performing turn operations by getting trained in predicting static/dynamic models. The goal is to initiate a self-driving machine, observing the surroundings across a transport region and act accordingly by the providers’ instructions. This initiative brings many real-world things to autonomous creature and the main purpose is to save time from user’s point of view. We implement a setup to make the machine act to various traffic scenarios and to track the user’s location via Latitude and Longitude provided by the user to reach the desired location.