Publication

EKF-based 3D SLAM for Structured Environment Reconstruction

Roland Siegwart, Jan Weingarten
2005
Conference Papers

Abstract

This paper presents the extension and experimental validation of the widely used EKF1-based SLAM2 algorithm to 3D space. It uses planar features extracted probabilistically from dense three-dimensional point clouds generated by a rotating 2D laser scanner. These features are represented in compliance with the Symmetries and Perturbation model (SPmodel) in a stochastic map. As the robot moves, this map is updated incrementally while its pose is tracked by using an Extended Kalman Filter. After showing how three-dimensional data can be generated, the probabilistic feature extraction method is described, capable of robustly extracting (infinite) planes from structured environments. The SLAM algorithm is then used to track a robot moving through an indoor environment and its capabilities in terms of 3D reconstruction are analyzed.

Official source

https://infoscience.epfl.ch/entities/publication/7f0c69de-7657-438b-9095-c08534feeb2a

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Roland Siegwart, Jan Weingarten
2005
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/7f0c69de-7657-438b-9095-c08534feeb2a

About this result

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