Smart Autonomous Indoor Navigation Robot Using ROS and LiDAR-Based SLAM

Abstract

This paper presents the design and real-world implementation of an indoor mobile robot capable of autonomous navigation using ROS, a Raspberry Pi 3 controller, and a TF Mini LiDAR sensor embedded on two servo motors (tilt and pan). The robot employs Simultaneous Localization and Mapping (SLAM) to build a 2D map of an unknown indoor environment while localizing itself within that map. A global planner (Rapidly-Exploring Random Tree, RRT) and local trajectory controller compute collision-free paths to user-defined goals. Ultrasonic rangefinders and the LiDAR provide real- time obstacle detection for reactive avoidance. We validated the system in a laboratory setting: the robot successfully mapped the area and autonomously navigated between waypoints without collisions. Our results demonstrate the effectiveness of low-cost sensors and open-source ROS software for learning foundational concepts of indoor robotics (localization, mapping, planning, and control). This work may aid educational and service applications in homes, hospitals, offices, etc., where autonomous mobile robots reduce manual labor (e.g., delivery of items, surveillance). The approach integrates sensor data processing, filter-based SLAM, and reactive path planning. Our results demonstrate effective localization and navigation performance consistent with recent literature.