Intelligent Systems: Public Forum

Registration is open! -- 2022 Intelligent Systems Workshop:

Registration is $150 for regular attendees and $25 for students. 

Please note that we are still accepting entries through July 15 for...

--The student poster and lightning talk competition: Students can submit their abstracts here. During the student sessions at the workshop, students will have the opportunity to present their research in 5-minute lightning talks or via posters. Research topics should be within the area of air and space intelligent systems. Students will have a chance to win cash awards ($1,000, $500, and $250 for 1st, 2nd, and 3rd place respectively). 

--The open mic session:  About 5-10 speakers will have the chance to present for ~5-7 minutes over lunch on July 27. This is a great opportunity to present your work or just give your opinion on a relevant topic. If you would like to present, please email your name and topic to Dani Selva dselva@tamu.edu.

Please join us in College Station TX on July 26-27, 2022 for a great program featuring keynote speakers Rob Ambrose (retired from 20 years of work at NASA JSC on autonomy/robotics, now Director for Space and Robotics Initiatives at TAMU/TEES) and Marc Steinberg (ONR Autonomy PM). The rest of the program includes 2 technical sessions with plenary speakers and panels on robust autonomy and human-machine teaming, breakout sessions, tours (including of the new Bush Combat Development Complex), a social, and of course, the crowd favorites: the student competition and the open mic session. Please visit https://aiaa-istc.github.io/2022_IS_Workshop.html for more information. (Please note that this workshop will be an in-person only event.) We hope to see you all there!

Please contact Dani Selva (dselva@tamu.edu) or John Valasek (valasek@tamu.edu) if you have any questions.

2nd Workshop on AI for Space in conjunction with ECCV 2022:

AI4Space focuses on the role of AI, particularly computer vision and machine learning, in helping to solve technical challenges related to space, from autonomous spacecraft, space mining, debris monitoring and mitigation, to answering fundamental questions about the universe. The workshop will highlight the space capabilities that draw from and/or overlap significantly with vision and learning research, outline the unique difficulties presented by space applications to vision and learning, and discuss recent advances towards overcoming those obstacles.

Website:

https://aiforspace.github.io/2022/

Call for Papers:

We solicit papers for AI4Space. Papers will be reviewed and accepted papers will be published in the proceedings of ECCV Workshops. Authors of accepted papers will also be invited to present at the workshop (in hybrid mode) at ECCV 2022, Tel-Aviv, late October 2022.

The general emphasis of AI4Space is vision and learning algorithms in off-Earth environments, including in the orbital region, surface and underground environments on other planetary bodies (e.g., the moon, Mars and asteroids), interplanetary space and solar system, and distant galaxies. Target application areas include autonomous spacecraft, space robotics, space traffic management, astronomy, astrobiology and cosmology. Emphasis is also placed on novel sensors and processing hardware for vision and learning in space, mitigating the challenges of the space environment towards vision and learning (e.g., solar radiation, extreme temperatures), and solving practical difficulties in vision and learning for space (e.g., lack of training data, unknown or partially known characteristics of operating environments).

A specific list of topics is as follows:
- Visual navigation for spacecraft operations
- Vision and learning for space robotics
- GPS-denied positioning on the moon and Mars
- Space debris monitoring and mitigation
- Vision and learning for astronomy, astrobiology and cosmology
- Novel sensors for space applications
- Processing hardware for vision and learning in space
- Mitigating challenges of the space environment to vision and learning
- Datasets, transfer learning and domain gap for space problems

Paper deadline:

11:59pm 15 July 2022

More details:

https://aiforspace.github.io/2022/