Fast, Automated, Photo realistic, 3D Modeling of Building Interiors
Abstract
GPS-denied indoor mobile mapping has been an active area of research for many years. With applications such as historical preservation, entertainment, and augmented reality, the demand for both fast and accurate scanning technologies has dramatically increased. In this project, we developed two algorithmic pipelines for GPS-denied indoor mobile 3D mapping using an ambulatory backpack system. By mounting scanning equipment on a backpack system, a human operator can traverse the interior of a building to produce a high-quality 3Dreconstruction. In each of our presented algorithmic pipelines, data from a number of 2D laser scanners, a camera, and an IMU is fused together to track the 3D position of the system as the operator traverses an unknown environment. This project presents a number of novel contributions f or indoor GPS-denied 2.5 and 3D mobile mapping using a number of 2D laser scanners, a camera, and an IMU. First, for 3Dmapping we develop a tightly coupled EKF estimator for fusing data from all sensors into a single optimized 3D trajectory. By formulating each sensor's contributions independently, we demonstrate a modular algorithm that easily scales to an arbitrary number of 2D laser scanners. In contrast to existing work that either assumes a known fixed map or limits the environment to a set of axis aligned planes, we demonstrate the ability to map environments containing horizontal and vertical planes of arbitrary orientation with no a priori information. Additionally, through timing and complexity analysis, we demonstrate that the runtime of the proposed EKF estimator is only linear in the acquisition time. Secondly, by including in our EKF estimator the laser scanner's spatial and temporal calibration parameters, we present a novel laser calibration methodology. Through simulated and real-world data, we validate that the proposed algorithms are capable of calibrating both the extrinsic and temporal misalignments present in our system's laser data.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 12, 2016
- Accession Number
- AD1027885
Entities
People
- Avideh Zakhor
Organizations
- University of California, Berkeley