activity
20192022
most citedPHASER: a Robust and Correspondence-free Global Pointcloud Registration

32 citations · 50 across the 6 of their papers we have counts for

collaborators

9 papers

cs.RO2022

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…

cs.RO2022

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…

cs.RO2022

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…

cs.RO20222 cited

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…

cs.RO2021

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…

cs.RO202132 cited

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…