Design And Construction of an Autonomous Mobile Robot for Indoor Navigation with Obstacles

Abstract

This paper presents the development of KARNAV, an autonomous mobile robot (AMR) prototype designed for indoor navigation with real-time obstacle detection and avoidance capabilities. The system leverages a ROS~2-based architecture to integrate LiDAR and inertial measurement unit (IMU) data, supporting advanced sensor fusion and SLAM-based (Simultaneous Localization and Mapping) localization. The design prioritizes the use of low-cost, accessible components without compromising operational reliability, demonstrating both technical and economic feasibility for industrial and academic applications. Experimental results validate the platform's ability to achieve robust navigation, energy efficiency, and adaptability within dynamic environments. This prototype provides a versatile foundation for further research in industrial robotics and the deployment of autonomous systems in complex indoor scenarios.