[robotics-worldwide] [meetings] 2nd Call for Papers: ICRA 2020 Workshop "Emerging Learning and Algorithmic Methods for Data Association in Robotics"

Kaveh Fathian kavehf at mit.edu
Thu Mar 5 18:52:55 PST 2020

Second Call for Papers

ICRA 2020 Workshop on Emerging Learning and Algorithmic Methods for Data
Association in Robotics
Location: Paris, France

Important Dates
Submission Deadline:  April 3, 2020, 23:59 EST
Acceptance Notification:  April 24, 2020
Workshop:  May 31, 2020

URL: https://urldefense.com/v3/__https://sites.google.com/view/edat/home__;!!LIr3w8kk_Xxm!5jo6fOjk-vd0Kw0p7DvkrTZcwJXF5pbhAqRg1wsfFNUnI5VpW1yE42vElORbKAp8WHbJATQg$ 

- Methods for outlier rejection and resilient data association
- Optimization and relaxation techniques for data association
- Machine learning methods with neural or statistical models
- Methods based on synergetic mathematical and learned models
- Point cloud alignment, sensor registration, fusion, and map merging
- Semantic segmentation, object detection, and pose estimation from images
or point clouds
- Applications of perception and data association algorithms in autonomous
vehicles, robotic manipulation, localization, and mapping

Data association, which can be described as identifying relations between
sets of measurements, physical objects, labels, etc., is a well-studied
field with solutions dating back to 70’s. However, recent results in the
fields of optimization, graph theory, and machine learning have opened new
and exciting research directions. This workshop aims to present the latest
results and emerging learning and algorithmic techniques for data
association in robotics. Through a series of contributed and invited talks
by academic leaders and renowned researchers, emerging algorithmic methods
based on optimization or graph theory, learning and end-to-end solutions
based on deep neural networks, and the synergy between them will be
discussed. These techniques promise new capabilities and performance
improvements across a broad range of applications, including but not
limited to semantic segmentation, point cloud alignment, sensor fusion for
autonomous vehicles, object pose estimation for robotic manipulation, place
recognition for simultaneous localization and mapping, and data fusion for
multi-agent systems. The workshop will further facilitate discussion on
current challenges and research directions in the next 5-10 years.

Nikolay Atanasov (UC San Diego)
Randal Beard (Brigham Young University)
Florian Bernard (Max Planck Institute)
Cesar Cadena (ETH Zurich)
Luca Carlone (MIT)
Kostas Daniilidis (University of Pennsylvania)
Jonathan How (MIT)
Ayoung Kim (KAIST)
John Leonard (MIT)
Juan Nieto (ETH Zurich)
Nicholas Roy (MIT)
Roberto Tron (Boston University)
Xiaowei Zhou (Zhejiang University)

We cordially invite researchers to submit short papers, extended abstracts,
or reports. Submitted contributions can describe work in progress,
preliminary results, novel concepts, or applications in industry. All
manuscripts are limited to 4 pages and should use the IEEE standard
two-column conference format (paper template available on the IEEE ICRA
2020 website). We encourage authors to submit a video clip to complement
their manuscript. Submissions will be selected based on their originality,
relevance to the workshop topics, contributions, technical clarity, and
presentation. All accepted manuscripts will be presented as posters during
three poster sessions that are spread out throughout the workshop schedule.
The top four contributions will be given 15 minutes to present their work
during two spotlight sessions.

To submit your contributions please follow:

Kaveh Fathian (MIT) - Corresponding organizer
Jonathan How (MIT)
Alec Koppel (Army Research Laboratory)
Ethan Stump (Army Research Laboratory)
Roberto Tron (Boston University)

Please contact the corresponding organizer with any questions.
More information at:

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