[Call for Papers] (Due June 15) RSS 2024 Full Day Workshop on Semantics for Robotics: From Environment Understanding and Reasoning to Safe Interaction External
Federico Pizarro Bejarano
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 (Due June 15th 2024).
Summary
- 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
Suggested Length: minimum 2 and maximum 4 pages excluding references
Style Template: https://roboticsconference.org/docs/paper-template-latex.tar.gz (RSS paper template)
Speakers
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