71 citations · 229 across the 12 of their papers we have counts for
14 papers · 1 filter
CompSLAM: Complementary Hierarchical Multi-Modal Localization and Mapping for Robot Autonomy in Underground Environments
Shehryar Khattak, Timon Homberger, Lukas Bernreiter +5
Robot autonomy in unknown, GPS-denied, and complex underground environments requires real-time, robust, and accurate onboard pose estimation and mapping for reliable operations. Th…
maplab 2.0 -- A Modular and Multi-Modal Mapping Framework
Andrei Cramariuc, Lukas Bernreiter, Florian Tschopp +5
Integration of multiple sensor modalities and deep learning into Simultaneous Localization And Mapping (SLAM) systems are areas of significant interest in current research. Multi-m…
A Framework for Collaborative Multi-Robot Mapping using Spectral Graph Wavelets
Lukas Bernreiter, Shehryar Khattak, Lionel Ott +3
The exploration of large-scale unknown environments can benefit from the deployment of multiple robots for collaborative mapping. Each robot explores a section of the environment a…
SphNet: A Spherical Network for Semantic Pointcloud Segmentation
Lukas Bernreiter, Lionel Ott, Roland Siegwart +1
Semantic segmentation for robotic systems can enable a wide range of applications, from self-driving cars and augmented reality systems to domestic robots. We argue that a spherica…
Present and Future of SLAM in Extreme Underground Environments
Kamak Ebadi, Lukas Bernreiter, Harel Biggie +28
This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT co…
Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
Marco Tranzatto, Mihir Dharmadhikari, Lukas Bernreiter +33
This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with…
Collaborative Robot Mapping using Spectral Graph Analysis
Lukas Bernreiter, Shehryar Khattak, Lionel Ott +3
In this paper, we deal with the problem of creating globally consistent pose graphs in a centralized multi-robot SLAM framework. For each robot to act autonomously, individual onbo…
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto, Frank Mascarich, Lukas Bernreiter +38
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy h…
Spherical Multi-Modal Place Recognition for Heterogeneous Sensor Systems
Lukas Bernreiter, Lionel Ott, Juan Nieto +2
In this paper, we propose a robust end-to-end multi-modal pipeline for place recognition where the sensor systems can differ from the map building to the query. Our approach operat…
3D3L: Deep Learned 3D Keypoint Detection and Description for LiDARs
Dominic Streiff, Lukas Bernreiter, Florian Tschopp +2
With the advent of powerful, light-weight 3D LiDARs, they have become the hearth of many navigation and SLAM algorithms on various autonomous systems. Pointcloud registration metho…
PHASER: a Robust and Correspondence-free Global Pointcloud Registration
Lukas Bernreiter, Lionel Ott, Juan Nieto +2
We propose PHASER, a correspondence-free global registration of sensor-centric pointclouds that is robust to noise, sparsity, and partial overlaps. Our method can seamlessly handle…
Multiple Hypothesis Semantic Mapping for Robust Data Association
Lukas Bernreiter, Abel Gawel, Hannes Sommer +3
In this paper, we present a semantic mapping approach with multiple hypothesis tracking for data association. As semantic information has the potential to overcome ambiguity in mea…
Accurate Mapping and Planning for Autonomous Racing
Leiv Andresen, Adrian Brandemuehl, Alex Hönger +11
This paper presents the perception, mapping, and planning pipeline implemented on an autonomous race car. It was developed by the 2019 AMZ driverless team for the Formula Student G…
VersaVIS: An Open Versatile Multi-Camera Visual-Inertial Sensor Suite
Florian Tschopp, Michael Riner, Marius Fehr +7
Robust and accurate pose estimation is crucial for many applications in mobile robotics. Extending visual Simultaneous Localization and Mapping (SLAM) with other modalities such as…