Multi-Sensor Integration for Indoor 3D Reconstruction

TL;DR

This paper introduces the Scannect, an innovative automatic system that fuses data from terrestrial laser scanners, Microsoft Kinect, and inertial measurement units to enable accurate, rapid indoor 3D mapping for navigation and environment modeling.

Contribution

It presents the first joint static-kinematic indoor 3D mapping system integrating multiple sensors for improved indoor environment reconstruction.

Findings

Successfully fused multiple sensor data for indoor mapping

Achieved accurate and rapid 3D reconstructions

Demonstrated system's effectiveness in various indoor environments

Abstract

Outdoor maps and navigation information delivered by modern services and technologies like Google Maps and Garmin navigators have revolutionized the lifestyle of many people. Motivated by the desire for similar navigation systems for indoor usage from consumers, advertisers, emergency rescuers/responders, etc., many indoor environments such as shopping malls, museums, casinos, airports, transit stations, offices, and schools need to be mapped. Typically, the environment is first reconstructed by capturing many point clouds from various stations and defining their spatial relationships. Currently, there is a lack of an accurate, rigorous, and speedy method for relating point clouds in indoor, urban, satellite-denied environments. This thesis presents a novel and automatic way for fusing calibrated point clouds obtained using a terrestrial laser scanner and the Microsoft Kinect by integrating them with a low-cost inertial measurement unit. The developed system, titled the Scannect, is the first joint static-kinematic indoor 3D mapper.