ICRA 2021 Workshop
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Title: 1st Advanced Marine Robotics TC Workshop: Active Perception
Date: June 4th (full day)
Location: Virtual Workshop
Website:
https://dartmouthrobotics.github.io/icra-2021-uw-active-perception/Contact: Corina Barbalata
cbarb...@lsu.eduIMPORTANT DATES
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April 30th: Submission deadline, 23:59 AoE
May 16th (rolling basis): Notification of acceptance
May 28th: Camera ready paper, 23:59pm AoE
June 4th: Workshop (full-day)
Link to call for papers:
https://dartmouthrobotics.github.io/icra-2021-uw-active-perception/call-for-papersFORMAT
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Authors are required to submit a 4-8 pages paper as PDF in the standard
ICRA IEEE conference format. We encourage contributions of research
papers describing early research on emerging topics and early results. Note that these contributions are not archival. A video (up to 10 MB) can be added to supplement your paper. Videos are not mandatory. Rather it’s an opportunity to augment one’s paper to visibly showcase results. MPG, MPEG or MP4 video formats can be used.
Please submit your contribution via Microsoft CMT3 by the deadline.
SUBMISSION
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Submissions will be judged based on relevance to the workshop topics,
technical quality, and novelty. All submissions will go through a single-blind review process. Authors of accepted papers are expected to give a lightning talk (3 minutes) and to present a poster at the
workshop. A number of papers will be selected for a 15 minutes oral
presentation. All accepted papers will be available in the workshop
Website.
OVERVIEW
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This workshop's objective is to understand and share the current best practices and open challenges in active perception, i.e., decision-making and navigation based on perception inputs, specifically focusing in the extremely challenging marine domain. Advances towards this area are necessary to enable the study of the aquatic world, still largely unexplored, and consequently the understanding of how the environment is changing. This is recognized to be a priority by the United Nations Agenda 2020, which sets as a sustainable development goal, the oceans.
Achieving robust active perception is hard in the marine domain: underwater robots' perception and communication are very limited. This workshop will explore the robust integration of perception tasks/inputs to decision modules, towards a holistic robotic system. This poses several open questions: e.g., how to best encode or represent the acquired data for control or decision units? How to cope with noisy perception data? Are there preferred perception sensors or methods depending on the end application?
MAIN TOPICS
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We welcome contributions and work in progress related to active perception, including, but not limited to:
* Informative path planning and adaptive sampling.
* Visual control systems
* Environment modeling (bathymetry, 3D representation and mapping, SLAM).
* Sensor fusion and signal processing across different sensor domains (stereo vision,sonars, ...).
* Human-robot cooperation.
* Machine learning practices in any of the above topics.
* Heavily tested systems in field trials and best practices for deployment and data management (aquaculture, oil & gas, environmental monitoring, ...).
SPEAKERS
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Confirmation of speakers and topics will be done the 1st week of May 2021.
* Prof. M. Ani Hsieh - The Scalable Autonomous Robots (ScalAR) Lab, UPenn
* Dr. Stephanie Kemna - Maritime Robotics AS
* Dr. Matias Valdenegro Toro - German Research Center for Artificial Intelligence (DFKI)
* Dr. Erin M. Fischell - Woods Hole Oceanographic Institution (WHOI)
* Prof. Luz Abril Torres Mendez - Cinvestav -- Robotica y Manufactura Avanzada (RYMA)
Visit the preliminary program:
https://dartmouthrobotics.github.io/icra-2021-uw-active-perception/speakers ORGANIZING COMMITTEE
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* Prof. Francesco Maurelli, Jacobs University, Bremen, Germany
* Prof. Alberto Quattrini Li, Dartmouth College, NH, USA
* Prof. Corina Barbalata, Louisiana State University, LA, USA
* MSc. Arturo Gomez Chavez, Jacobs University, Bremen, Germany
* Prof. Hyun-Taek Choi, Korea Research Institute of Ships and Ocean, South Korea