Enhancement of obstacle detection and avoidance in smart cars using microcontrollers

Abstract

autonomous obstacle-avoiding robotic car designed for collision-free navigation. Several researches were conducted to address gaps such as distance covered by the sensor, power consumption, and mobility of the robot but gaps still exist. The aim of this research is to implement a robot car that, while moving, has the ability to detect obstacles in its path and change direction, the primary objective was to engineer a mobile platform capable of detecting environmental barriers and recalculating its trajectory without external human intervention. By utilizing an HC-SR04 ultrasonic sensor for distance measurement and an Arduino UNO microcontroller as the primary processing unit, the system continuously monitors its path through 40KHz sound wave pulses. Upon detecting an obstacle within a predefined threshold, the robot halts, scans its immediate surroundings via a servo-mounted sensor, and identifies the safest direction based on the maximum clear distance available. Experimental evaluations demonstrate a 90% success rate in navigating controlled environments containing various objects such as desks, chairs, and walls; it also utilized the HC-SR04 sensor to improve detection accuracy and minimise power consumption. This implementation serves as a scalable prototype for enhancing automotive safety and industrial automation, offering a cost-effective alternative to expensive LiDAR-based systems.