Cerberus in the darpa subterranean challenge

M Tranzatto, T Miki, M Dharmadhikari, L Bernreiter… - Science Robotics, 2022 - science.org
This article presents the core technologies and deployment strategies of Team CERBERUS
that enabled our winning run in the DARPA Subterranean Challenge finals. CERBERUS is a …

Present and future of slam in extreme environments: The darpa subt challenge

K Ebadi, L Bernreiter, H Biggie, G Catt… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
This article surveys recent progress and discusses future opportunities for simultaneous
localization and mapping (SLAM) in extreme underground environments. SLAM in …

Present and future of slam in extreme underground environments

K Ebadi, L Bernreiter, H Biggie, G Catt, Y Chang… - arXiv preprint arXiv …, 2022 - arxiv.org
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 …

A UAV-based explore-then-exploit system for autonomous indoor facility inspection and scene reconstruction

C Gao, X Wang, R Wang, Z Zhao, Y Zhai, X Chen… - Automation in …, 2023 - Elsevier
Traditional indoor facility inspections on pipelines and boilers are conducted manually and
can be logistically challenging, labor-intensive, costly, and dangerous for the inspectors …

Oxpecker: A tethered uav for inspection of stone-mine pillars

B Martinez Rocamora Jr, RR Lima, K Samarakoon… - Drones, 2023 - mdpi.com
This paper presents a state-of-the-art tethered unmanned aerial vehicle (TUAV) for structural
integrity assessment of underground stone mine pillars. The TUAV, powered by its tether …

Semantically-enhanced deep collision prediction for autonomous navigation using aerial robots

M Kulkarni, H Nguyen, K Alexis - 2023 IEEE/RSJ International …, 2023 - ieeexplore.ieee.org
This paper contributes a novel and modularized learning-based method for aerial robots
navigating cluttered environments containing hard-to-perceive thin obstacles without …

Learning Occluded Branch Depth Maps in Forest Environments Using RGB-D Images

C Geckeler, E Aucone, Y Schnider… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Covering over a third of all terrestrial land area, forests are crucial environments; as
ecosystems, for farming, and for human leisure. However, they are challenging to access for …

Mimosa: A multi-modal slam framework for resilient autonomy against sensor degradation

N Khedekar, M Kulkarni, K Alexis - 2022 IEEE/RSJ International …, 2022 - ieeexplore.ieee.org
This paper presents a framework for Multi-Modal SLAM (MIMOSA) that utilizes a nonlinear
factor graph as the underlying representation to provide loosely-coupled fusion of any …

Semantics-aware exploration and inspection path planning

M Dharmadhikari, K Alexis - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
This paper contributes a novel strategy for semantics-aware autonomous exploration and
inspection path planning. Attuned to the fact that environments that need to be explored …

Residual dynamics learning for trajectory tracking for multi-rotor aerial vehicles

G Kulathunga, H Hamed, A Klimchik - Scientific Reports, 2024 - nature.com
This paper presents a technique to model the residual dynamics between a high-level
planner and a low-level controller by considering reference trajectory tracking in a cluttered …