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Keywords

Robotics, Computer Vision, Artificial Intelligence, Autonomous Systems

Biography

I'm a postodoctoral fellow at the MIT-SPARK Lab lead by Prof. Dr. Luca Carlone. I obtained my PhD at the Autonomous Systems Lab (ASL) lead by Prof. Dr. Roland Siegwart at ETH Zurich in 2022, in collaboration with the Microsoft Mixed Reality & AI Lab lead by Prof. Dr. Marc Pollefeys. Before that, I obtained my M.Sc. in Robotics, Systems, and Control (RSC) in 2019 also at ETH, which I graduated with distinction and was awarded the Willi Studer Prize for the best graduate and the ETH Medal for outstanding master theses.

My main research interest lies in autonomy for intelligent mobile systems. In particular, my work focuses on active and passive perception and understanding of changing environments for robotic interaction and augmented reality. This includes building dense geometric and semantic representations of an environment, scene abstraction and understanding, lifelong learning and mapping, as well as active path and interaction planning to build these representations and abstractions autonomously and in unknown environments.

Activities

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Employment (3)

Massachusetts Institute of Technology: Cambridge, MA, US

2023-02 to present | Postdoctoral Fellow (Department of Aeronautics and Astronautics)
Employment
Source: Self-asserted source
Lukas Schmid

ETH Zurich: Zurich, CH

2022-10 to 2023-01 | Postdoctoral Researcher (Department of Mechanical and Process Engineering)
Employment
Source: Self-asserted source
Lukas Schmid

ETH Zurich: Zurich, CH

2019-06 to 2022-10 | PhD Student (Department of Mechanical and Process Engineering)
Employment
Source: Self-asserted source
Lukas Schmid

Works (11)

Traversing Mars: Cooperative Informative Path Planning to Efficiently Navigate Unknown Scenes

IEEE Robotics and Automation Letters
2025-02 | Journal article
DOI: 10.1109/LRA.2024.3513036
Contributors: Friedrich M. Rockenbauer; Jaeyoung Lim; Marcus G. Müller; Roland Siegwart; Lukas Schmid
Source: check_circle
Crossref

Long-Term Human Trajectory Prediction Using 3D Dynamic Scene Graphs

IEEE Robotics and Automation Letters
2024-12 | Journal article
DOI: 10.1109/LRA.2024.3482169
Contributors: Nicolas Gorlo; Lukas Schmid; Luca Carlone
Source: check_circle
Crossref

Clio: Real-Time Task-Driven Open-Set 3D Scene Graphs

IEEE Robotics and Automation Letters
2024-10 | Journal article
DOI: 10.1109/LRA.2024.3451395
Contributors: Dominic Maggio; Yun Chang; Nathan Hughes; Matthew Trang; Dan Griffith; Carlyn Dougherty; Eric Cristofalo; Lukas Schmid; Luca Carlone
Source: check_circle
Crossref

Khronos: A Unified Approach for Spatio-Temporal Metric-Semantic SLAM in Dynamic Environments

Robotics: Science and Systems XX
2024-07-15 | Conference paper
DOI: 10.15607/rss.2024.xx.081
Contributors: Lukas Schmid; Marcus Abate; Yun Chang; Luca Carlone
Source: Self-asserted source
Lukas Schmid

Dynablox: Real-Time Detection of Diverse Dynamic Objects in Complex Environments

IEEE Robotics and Automation Letters
2023-10 | Journal article
DOI: 10.1109/LRA.2023.3305239
Contributors: Lukas Schmid; Olov Andersson; Aurelio Sulser; Patrick Pfreundschuh; Roland Siegwart
Source: check_circle
Crossref

Embodied Active Domain Adaptation for Semantic Segmentation via Informative Path Planning

IEEE Robotics and Automation Letters
2022-10 | Journal article
DOI: 10.1109/LRA.2022.3188901
Contributors: Rene Zurbrugg; Hermann Blum; Cesar Cadena; Roland Siegwart; Lukas Schmid
Source: check_circle
Crossref

Fast and Compute-Efficient Sampling-Based Local Exploration Planning via Distribution Learning

IEEE Robotics and Automation Letters
2022-07 | Journal article
DOI: 10.1109/LRA.2022.3186511
Contributors: Lukas Schmid; Chao Ni; Yuliang Zhong; Roland Siegwart; Olov Andersson
Source: check_circle
Crossref

A Unified Approach for Autonomous Volumetric Exploration of Large Scale Environments Under Severe Odometry Drift

IEEE Robotics and Automation Letters
2021-07 | Journal article
DOI: 10.1109/LRA.2021.3068954
Contributors: Lukas Schmid; Victor Reijgwart; Lionel Ott; Juan Nieto; Roland Siegwart; Cesar Cadena
Source: check_circle
Crossref

An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments

IEEE Robotics and Automation Letters
2020-04 | Journal article
DOI: 10.1109/LRA.2020.2969191
Contributors: Lukas Schmid; Michael Pantic; Raghav Khanna; Lionel Ott; Roland Siegwart; Juan Nieto
Source: check_circle
Crossref

A spatio temporal spectral framework for plant stress phenotyping

Plant Methods
2019-12 | Journal article
DOI: 10.1186/s13007-019-0398-8
Part of ISSN: 1746-4811
Source: Self-asserted source
Lukas Schmid

An Approach for Semantic Segmentation of Tree-like Vegetation

2019 International Conference on Robotics and Automation (ICRA)
2019-05 | Conference paper
DOI: 10.1109/icra.2019.8793576
ISBN: 9781538660270
Source: Self-asserted source
Lukas Schmid
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