Design and Implementation of an Autonomous Differential Drive Mobile Robot with Obstacle Avoidance Using Arduino Nano

Abstract

This paper presents the design and implementation of an autonomous mobile robot capable of navigating unknown environments through maze-solving algorithms and dynamic obstacle avoidance. The primary objective is to engineer a low-cost Automated Guided Vehicle (AGV) that integrates environmental perception with real-time decision-making. The system architecture utilizes a differential drive chassis configuration, driven by two DC gear motors. Unlike servo-steering systems, directional control is achieved by varying the speed and direction of the independent rear motors (skid-steering). The central processing unit, an Arduino Nano, interfaces with a distributed sensor array consisting of three downward-facing infrared (IR) sensors for path tracking and one forward-facing IR sensor for collision prevention. The control software implements the "Left-Hand Rule" algorithm for traversing simply connected mazes and a "Smart Avoidance" subroutine that enables the robot to autonomously reroute when facing physical obstructions. Additionally, the system incorporates a Human-Machine Interface (HMI) utilizing an I2C-enabled Liquid Crystal Display (LCD) and LED indicators to provide diagnostic feedback during operation.