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Michael Brünig

4 accepted papers

2025

Online 6DoF Global Localisation in Forests using Semantically-Guided Re-Localisation and Cross-View Factor-Graph Optimisation

Lucas Carvalho de Lima, Ethan Griffiths, Maryam Haghighat, Simon Denman, Clinton Fookes, Paulo V. K. Borges +2
IROS 2025

This paper presents FGLoc6D, a novel approach for robust global localisation and online 6DoF pose estimation of ground robots in forest environments by leveraging deep semantically-guided re-localisation and cross-view factor graph optimisation. The proposed method addresses the challenges of aligni

Cited by 2Source ↗Scholar ↗
2024

Under-Canopy Navigation Using Aerial Lidar Maps

Lucas Carvalho de Lima, Nicholas R. J. Lawrance, Kasra Khosoussi, Paulo V. K. Borges, Michael Brünig
RA-L 2024

Autonomous navigation in unstructured natural environments poses a significant challenge. In goal navigation tasks without prior information, the limited look-ahead of onboard sensors utilised by robots compromises path efficiency. We propose a novel approach that leverages an above-the-canopy aeria

Cited by 2Source ↗Scholar ↗
2023

Air-Ground Collaborative Localisation in Forests Using Lidar Canopy Maps

Lucas Carvalho de Lima, Milad Ramezani, Paulo Vinicius Koerich Borges, Michael Brünig
RA-L 2023

Geo-localisation in GPS-poor environments such as forests is crucial in field robotics and remains a challenge. To tackle this problem, we introduce a collaborative localisation framework that fuses ‘above canopy’ height information obtained from airborne aggregated lidar scans, as a reference map,

Cited by 14Source ↗Scholar ↗