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HectorGrapher: Continuous-time Lidar SLAM with Multi-resolution Signed Distance Function Registration for Challenging Terrain

Daun, Kevin ; Schnaubelt, Marius ; Kohlbrecher, Stefan ; Stryk, Oskar von (2021):
HectorGrapher: Continuous-time Lidar SLAM with Multi-resolution Signed Distance Function Registration for Challenging Terrain.
2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), New York, USA, 25.-27.10.2021, [Conference or Workshop Item]

Abstract

For deployment in previously unknown, unstructured, and GPS-denied environments, autonomous mobile rescue robots need to localize themselves in such environments and create a map of it using a simultaneous localization and mapping (SLAM) approach. Continuous-time SLAM approaches represent the pose as a time-continuous estimate that provides high accuracy and allows correcting for distortions induced by motion during the scan capture. To enable robust and accurate real-time SLAM in challenging terrain, we propose HectorGrapher which enables accurate localization by continuous-time pose estimation and robust scan registration based on multi-resolution signed distance functions. We evaluate the method in multiple publicly available real-world datasets, as well as a data set from the RoboCup 2021 Rescue League, where we applied the proposed method to win the Best-in-Class "Exploration and Mapping" Award.

Item Type: Conference or Workshop Item
Erschienen: 2021
Creators: Daun, Kevin ; Schnaubelt, Marius ; Kohlbrecher, Stefan ; Stryk, Oskar von
Title: HectorGrapher: Continuous-time Lidar SLAM with Multi-resolution Signed Distance Function Registration for Challenging Terrain
Language: English
Abstract:

For deployment in previously unknown, unstructured, and GPS-denied environments, autonomous mobile rescue robots need to localize themselves in such environments and create a map of it using a simultaneous localization and mapping (SLAM) approach. Continuous-time SLAM approaches represent the pose as a time-continuous estimate that provides high accuracy and allows correcting for distortions induced by motion during the scan capture. To enable robust and accurate real-time SLAM in challenging terrain, we propose HectorGrapher which enables accurate localization by continuous-time pose estimation and robust scan registration based on multi-resolution signed distance functions. We evaluate the method in multiple publicly available real-world datasets, as well as a data set from the RoboCup 2021 Rescue League, where we applied the proposed method to win the Best-in-Class "Exploration and Mapping" Award.

Uncontrolled Keywords: emergenCITY_CPS
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
TU-Projects: Bund/BMBF|13N14861|A-DRZ
HMWK|III L6-519/03/05.001-(0016)|emergenCity TP Bock
Event Title: 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Event Location: New York, USA
Event Dates: 25.-27.10.2021
Date Deposited: 11 Nov 2021 07:15
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