An IoT based Obstacle Detection, Line Following and GPS Tracking Robot using LabVIEW

Abstract

The tactics created for autonomous automobiles in this study include collision detection and line following. The most popular use of Internet of Things (IoT) technology in intelligent transportation is self-driving. When autonomous cars drive themselves, they won't make sudden lane changes. The goal of the project is to construct a robotic automobile that avoids obstacles by using an ultrasonic sensor. ESP32 is used in order to get the desired result. A robot is a machine designed to do tasks either independently or under guidance. The robot moves in a different direction when the ESP32 uses a motor driver to turn on the robot's motors. The goal is to build an artificially intelligent robotic vehicle that can self-direct when it comes across an obstacle. By employing an obstacle sensor (HC-SR04) to detect and prevent collisions, this robot can navigate to its intended location. It is an autonomous car that can distinguish between a black and white path and follows it. The robot tracks the path using an infrared sensor that is integrated inside it. After receiving instructions from ESP32, the robot is programmed to identify a line and attempt to travel in the direction of its target. For this project, the position of the vehicle is ascertained via a Global Positioning System (GPS) module. The patch antenna of the GPS module determines the robot's coordinates, which are transmitted to the IoT Cloud (real-time database) so that LabVIEW may be used to see and monitor the robot. Time may be saved by using the proposed robotic techniques, which require less manual effort and greater efficiency. Because of this, the robot is designed to travel a predefined path, avoiding obstacles along the way, until it arrives at its objective. It could also track the robot's whereabouts using the GPS module's coordinates.