/GravityFusion: Real-time Dense mapping without Pose Graph using Deformation and Orientation

GravityFusion: Real-time Dense mapping without Pose Graph using Deformation and Orientation

Puneet Puri, Daoyuan Jia and Michael Kaess
Conference Paper, IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS, September, 2017

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Abstract

In this paper, we propose a novel approach to integrating inertial sensor data into a pose-graph free dense mapping algorithm that we call GravityFusion. A range of dense mapping algorithms have recently been proposed, though few integrate inertial sensing. We build on ElasticFusion, a particularly elegant approach that fuses color and depth information directly into small surface patches called surfels. Traditional inertial integration happens at the level of camera motion, however, a pose graph is not available here. Instead, we present a novel approach that incorporates the gravity measurements directly into the map: Each surfel is annotated by a gravity measurement, and that measurement is updated with each new observation of the surfel. We use mesh deformation, the same mechanism used for loop closure in ElasticFusion, to enforce a consistent gravity direction among all the surfels. This eliminates drift in two degrees of freedom, avoiding the typical curving of maps that are particularly pronounced in long hallways, as we qualitatively show in the experimental evaluation.

BibTeX Reference
@conference{Puri-2017-27295,
author = {Puneet Puri and Daoyuan Jia and Michael Kaess},
title = {GravityFusion: Real-time Dense mapping without Pose Graph using Deformation and Orientation},
booktitle = {IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, IROS},
year = {2017},
month = {September},
}
2017-09-13T10:37:58+00:00