[Call for Papers] RSS 2024 Full Day Workshop on Semantics for Robotics: From Environment Understanding and Reasoning to Safe Interaction External

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Federico Pizarro Bejarano

May 30, 2024, 8:43:07 PMMay 30
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Dear all,

We are delighted to announce our upcoming RSS 2024 Full Day Workshop on Semantics for Robotics: From Environment Understanding and Reasoning to Safe Interaction, to be held at the Delft University of Technology, Delft, Netherlands, on July 15, 2024. We would like to invite you to participate and contribute your research in the form of short paper submissions. 


- Workshop Website: https://www.dynsyslab.org/rss24-workshop-on-semantics-for-robotics/

- CMT Submission Page: https://tiny.cc/RSS24SfR 

- Initial Submission: June 15, 2024, 11:59 pm AoE

- Author Notification: June 30, 2024

Workshop Overview

For robots to safely interact with people and the real world, they need the capability to not only perceive but also understand their surroundings in a semantically meaningful way. Additionally, reliably exploiting semantic information requires tightly coupled perception, learning, and control algorithm design. Advanced perception methods coupled with learning algorithms have made significant progress in enabling semantic understanding. Recent breakthroughs in foundation models have further exposed opportunities for robots to contextually reason about their operating environments. By organizing this workshop, we hope to foster discussions on innovative approaches that harness semantic understanding for the design and deployment of intelligent embodied systems. We aim to facilitate an interdisciplinary exchange between researchers in robot learning, perception, mapping, and control to identify the opportunities and pressing challenges when incorporating semantics into robotic applications.

Call for Papers

We are inviting researchers from different disciplines to share novel ideas and ideas on topics pertinent to the workshop themes, which include but are not limited to:

  • Perception methods incorporating semantic, geometric, and multi-modal information 

  • Efficient 3D object and environment representations from multi-modal sensor inputs

  • Uncertainty estimation for robust 3D perception 

  • Contextual reasoning of the 3D environments 

  • Safe motion planning and control under semantic uncertainties

  • Robot skill acquisition and learning leveraging semantics information

  • Multi-agent collaboration through semantic information

  • Demonstration or position papers on foundation-model-based perception and decision-making methods

The review process will be single-blind. Accepted papers will be published on the workshop webpage and will be presented as a spotlight talk or as a poster.

Paper Format


Michael Milford, Queensland University of Technology (QUT)

Luca Carlone, Massachusetts Institute of Technology (MIT)

Angela Dai, Technical University of Munich (TUM)

Oier Mees, University of California, Berkeley (UCB)

Masha Itkina, Toyota Research Institute (TRI)

Marco Pavone, Stanford University and Nvidia

Andrea Bajcsy, Carnegie Mellon University (CMU)

Koushil Sreenath, University of California, Berkeley (UCB)

Manuel Keppler, German Aerospace Center (DLR)

Federico Tombari, Google and Technical University of Munich (TUM)

Organizing Committee

Angela P. Schoellig, Technical University of Munich

SiQi Zhou, Technical University of Munich

Lukas Brunke, Technical University of Munich

Adam Hall, University of Toronto

Federico Pizarro Bejarano, University of Toronto

Jingxing Qian, University of Toronto

Sepehr Samavi, University of Toronto

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