Timo Röhling — accepted AI-conference papers

2020

OverlapNet: Loop Closing for LiDAR-based SLAM

Xieyuanli Chen, Thomas Läbe, Andres Milioto, Timo Röhling, Olga Vysotska, Alexandre Haag +2

RSS 2020poster

Simultaneous localization and mapping (SLAM) is a fundamental capability required by most autonomous systems. In this paper, we address the problem of loop closing for SLAM based on 3D laser scans recorded by autonomous cars. Our approach utilizes a deep neural network exploiting different cues gene…

Cited by 306 Source ↗PDF ↗code ↗Scholar ↗

2015

A fast histogram-based similarity measure for detecting loop closures in 3-D LIDAR data

Timo Röhling, Jennifer Mack, Dirk Schulz

IROS 2015poster

We present a fast method of detecting loop closure opportunities through the use of similarity measures on histograms extracted from 3-D LIDAR data. We avoid computationally expensive features and compute histograms over simple global statistics of the LIDAR scans. The resulting histograms encode su…

Cited by 115 Source ↗Scholar ↗