Autonomous Indoor Navigation Robot Using LIDAR-Based SLAM

Problem statement

Navigating unknown indoor spaces autonomously is challenging due to the absence of GPS and dynamically changing environments. Traditional robots rely on pre-mapped environments, which limits flexibility. A robot capable of mapping and navigating in real time is essential for industrial automation and service robotics.

Abstract

This project implements an indoor autonomous navigation robot using LIDAR-based Simultaneous Localization and Mapping (SLAM). A Raspberry Pi or Jetson Nano collects LIDAR scans, builds a live map using SLAM algorithms, and calculates the robot's position. A path planning module identifies optimal routes while obstacle avoidance ensures safe travel. The robot can be deployed for industrial inspection, warehouse automation, and campus navigation.

Components required

• LIDAR Module (RPLidar A1/A2)
• Raspberry Pi / Jetson Nano
• Motor Driver (L298N)
• DC Motors / Encoders
• Battery Pack
• ROS (Robot Operating System)

Block diagram

Working

The LIDAR continuously scans the area and sends distance measurements to the SLAM module. SLAM builds a map and simultaneously localizes the robot within it. The path planner computes the shortest obstacle-free path to the destination. The motor control unit adjusts wheel speeds to follow the generated path while avoiding dynamic obstacles.

Applications

• Warehouse robots
• Hospital delivery robots
• Campus indoor navigation
• Search and rescue operations
• Industrial inspection