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update team, pubs, and teaching
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_data/papers.bib

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@@ -7,8 +7,49 @@ @string{CoRL
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@string{AuRo = {Autonomous Robots (AuRo)}}
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@string{TRO = {IEEE Transactions on Robotics (T-RO)}}
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@string{RAL = {IEEE Robotics and Automation Letters (R-AL)}}
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@string{L4DC = {Learning for Dynamics and Controls (L4DC)}}
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@string{AAMAS = {International Conference on Autonomous Agents and Multiagent Systems (AAMAS)}}
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@string{preprint = {Under Review}}
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@article{2026-ann-cmcgs,
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title={ANN-CMCGS: Generalizing Continuous Monte-Carlo Graph Search with Approximate Nearest Neighbors},
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author={Christoph Scherer and
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Wolfgang Hönig},
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journal=AAMAS,
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year={2026},
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}
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@article{2026-cfbf-model,
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title={How to Model Your Crazyflie Brushless},
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author={Alexander Gräfe and
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Christoph Scherer and
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Wolfgang Hönig and
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Sebastian Trimpe},
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journal=ICRA,
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year={2026},
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}
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@article{2026-grace,
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title={GRACE: A Unified 2D Multi-Robot Path Planning Simulator & Benchmark for Grid, Roadmap, And Continuous Environments},
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author={Chuanlong Zang and
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Anna Mannucci and
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Isabelle Barz and
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Philipp Schillinger and
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Florian Lier and
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Wolfgang Hönig},
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journal=ICRA,
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year={2026},
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}
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@article{2026-orn-cbf,
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title={ORN-CBF: Learning Observation-conditioned Residual Neural Control Barrier Functions via Hypernetworks},
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author={Bojan Derajic and
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Sebastian Bernhard and
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Wolfgang Hönig},
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journal=ICRA,
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year={2026},
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}
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@article{2025-db-lacam,
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title={db-LaCAM: Fast and Scalable Multi-Robot Kinodynamic Motion Planning with Discontinuity-Bounded Search and Lightweight MAPF},
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Sayantan Auddy and
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Marc Toussaint and
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Wolfgang Hönig},
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journal=preprint,
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journal=ICRA,
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arxiv={2509.14126},
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year={2025},
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year={2026},
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video={https://youtu.be/0gBlbA2pX4g},
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}
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author={Eckart Cobo-Briesewitz and
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Khaled Wahba and
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Wolfgang Hönig},
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journal=preprint,
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journal=L4DC,
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arxiv={2503.09441},
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year={2025}
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year={2026}
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}
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@ARTICLE{spencer2025,

_data/teaching.yml

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# More details on request.
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- name: "Active Learning for Tuning Controller Parameters (MS)"
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note: |
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The goal of this thesis is to develop an active learning algorithm that can effectively automatically tune controller gains. The key idea is to tune the gains in simulation and incrementally improve the quality of the simulation accuracy by collecting data on the real platform. Active learning is used to automatically compute experiments to be executed on the physical platform that promise to improve the simulator accuracy most significantly.
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# - name: "Active Learning for Tuning Controller Parameters (MS)"
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# note: |
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# The goal of this thesis is to develop an active learning algorithm that can effectively automatically tune controller gains. The key idea is to tune the gains in simulation and incrementally improve the quality of the simulation accuracy by collecting data on the real platform. Active learning is used to automatically compute experiments to be executed on the physical platform that promise to improve the simulator accuracy most significantly.
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This is a joint thesis with the LIS group (Prof. Toussaint) and requires knowledge in machine learning, motion planning, and controls.
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# This is a joint thesis with the LIS group (Prof. Toussaint) and requires knowledge in machine learning, motion planning, and controls.
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If you are interested in the topic, please contact <a href="mailto:office@mrs.tu-berlin.de">Wolfgang Hönig</a> with a motivation letter. In your letter, please describe why you are interested and your technical background. We are a highly interdisciplinary and diverse team and we explicitly encourage applications from underrepresented groups.
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# If you are interested in the topic, please contact <a href="mailto:office@mrs.tu-berlin.de">Wolfgang Hönig</a> with a motivation letter. In your letter, please describe why you are interested and your technical background. We are a highly interdisciplinary and diverse team and we explicitly encourage applications from underrepresented groups.
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pdf: assets/pdf/2026_ms_topic_active_learning.pdf
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apply: |
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mailto: office@mrs.tu-berlin.de?subject=Application for Active Learning MS Thesis&body=Please write in plain text or attach a single PDF with your motivation letter
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# pdf: assets/pdf/2026_ms_topic_active_learning.pdf
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# apply: |
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# mailto: office@mrs.tu-berlin.de?subject=Application for Active Learning MS Thesis&body=Please write in plain text or attach a single PDF with your motivation letter
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- name: Open Topic
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note: |

_data/team.yml

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github: Vincentive1232
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image: jiaming_li.jpg
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start: 07/2025
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end: 01/2026
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- name: Charlotte Stentzler
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role: Student Assistant
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- name: Issa-Noel Yamamura
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role: High School Student
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start: 01/2026
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start: 01/2026
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end: 01/2026

_layouts/bib.html

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<div class="tile is-parent">
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{% endcomment %}
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<div class="tile is-child card">
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{% assign filename = entry.key | append: '.jpg' %}
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{% assign img_file_exists = site.static_files | find: "name", filename %}
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{% if img_file_exists %}
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<div class="card-image has-text-centered">
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<figure class="image is-inline-block">
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<img src="assets/img/{{entry.key}}.jpg" alt="Paper image">
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</figure>
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{% endif %}
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<div class="card-content paper">
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<p class="title">
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{{entry.title}}

index.html

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<h2 class="subtitle is-6">News</h2>
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<ul>
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<li>
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<span class="title">One AAMAS, one L4DC, and 4 ICRA papers accepted.</span>
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<span class="note">01/2026</span>
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</li>
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<li>
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<span class="title">One <a href="https://doi.org/10.1109/TRO.2025.3637148">paper</a> at T-RO accepted.</span>
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<span class="note">11/2025</span>

teaching.html

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</ul>
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</div> -->
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<div class="section-heading">
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<h2 class="title is-2">Summer 2026</h2>
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</div>
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<div class="container">
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We do not offer any classes this term. If you are interested in robotics, please join the interest group.
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</div>
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<div class="section-heading">
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<h2 class="title is-2">Winter 2025/26</h2>
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</div>

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