3rd Workshop on AI for Space
In conjunction with CVPR 2024
Date: June 17 or 18, 2024
Venue: Seattle Convention Center
The space sector is experiencing significant growth. Currently planned activities and utilisation models also greatly exceed the scope, ambition and/or commercial value of space missions in the previous century, e.g., autonomous satellites for earth observation, on-orbit servicing, intelligent rovers for planetary exploration, and space traffic management and debris mitigation. Achieving these ambitious goals requires surmounting non-trivial technical obstacles. AI4Space focuses on the role of AI, particularly computer vision and machine learning, in helping to solve those technical hurdles. 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.
Call for Papers
We solicit papers for AI4Space. The general emphasis of AI4Space is vision and learning algorithms for autonomous space systems, which operate in the Earth’s orbital regions, cislunar orbit, planetary bodies (e.g., the moon, Mars and asteroids), and interplanetary space. Emphasis is also placed on novel sensors and processors for vision and learning in space, mitigating the challenges of the space environment towards vision and learning (e.g., radiation, extreme temperatures), and fundamental difficulties in vision and learning for space (e.g., lack of training data, unknown operating environments).
A specific list of topics is as follows:
- Vision and learning for spacecraft navigation and operations (e.g., rendezvous, proximity operations, docking, space maneuvers, entry descent landing).
- Vision and learning for space robots (e.g., rovers, UAVs, UGVs, UUWs) and multi-agent systems.
- Mapping and global positioning on planetary bodies (moon, Mars, asteroids), including celestial positioning.
- Onboard AI for Earth observation applications (e.g. near-real-time disaster monitoring, distributed learning on satellites, tip and cue satellite-based systems).
- Onboard AI for satellite operations (e.g. AI-based star trackers, fault detection isolation and recovery).
- Space debris monitoring and mitigation.
- Sensors for space applications (e.g., optical, multispectral, lidar, radar, neuromorphic).
- Onboard compute hardware for vision and learning (e.g., neural network accelerators, neuromorphic processors).
- Mitigating challenges of the space environment (e.g., radiation, thermal) to vision and learning systems.
- Datasets, transfer learning and domain gap.
Things to note:
- Papers will be fully peer reviewed and accepted papers will be published in the proceedings of CVPR 2024 Workshops.
- AI4Space follows the submission policies of CVPR 2024. An implication is that submissions to AI4Space should be sufficiently original works not under consideration/reviewing in other venues.
- Consistent with the submission policy, we highly encourage submission of papers relevant to AI4Space but are rejected from the main CVPR conference (decisions on Feb 27---before the AI4Space submission deadline on March 1).
- Accepted AI4Space papers are also expected to be presented in person at the workshop, which will be co-located with CVPR 2024.
- If you require a formal invitation letter to facilitate your travel to CVPR 2024 in Seattle, please visit the main conference page.
- All papers published via this workshop must be aimed towards the peaceful usage of AI for space.
Submissions must be in the CVPR format and are limited to 8 pages excluding references. Please refer to the main conference's submission guildelines for more details, and do not hesitate to contact the lead organiser Tat-Jun Chin if you have any questions.
Reviewing is double blind - remember to remove your names and affiliations in the submitted version (selecting the reviewing option in the LaTeX template will take care of that). Accepted works will be published in the CVPR 2024 workshop proceedings.
We are excited to co-host an AI for space challenge, SPARK 2024, which follows from the successful previous editions of the event at AI4Space @ ECCV 2022. The latest edition of SPARK (SPAcecraft Recognition leveraging Knowledge of Space Environment) aims to design data-driven approaches for spacecraft detection and trajectory estimation. SPARK will utilise data synthetically simulated with a game-based engine in addition to data collected from the Zero-G lab at the University of Luxembourg.
This year’s competition will include two streams:
- Stream-1: Detecting space objects in RGB images.
- Stream-2: Spacecraft trajectory estimation in a rendezvous scenario.
Final results and awards will be announced at AI4Space at CVPR 2024. Challenge winners may also be invited to present their methods at the workshop (subject to time availability in the finalised workshop program).
Important DatesAll times/dates below are in Pacific Standard Time (PST).
|Paper Submission Deadline
|March 1, 2024
|Paper Reviewing Starts
|March 6, 2024
|Paper Reviews Due
|March 27, 2024
|April 3, 2024
|April 14, 2024
The program will be progressively updated. At the moment, we have confirmed the following exciting Invited Speakers.
Soon-Jo Chung is Bren Professor of Control and Dynamical Systems in the California Institute of Technology. Prof. Chung is also a Senior Research Scientist of the Jet Propulsion Laboratory, which Caltech manages for NASA. He is the recipient of the University of Illinois Engineering Dean’s Award for Excellence in Research, the Arnold Beckman Faculty Fellowship of the University of Illinois Center for Advanced Study, the AFOSR Young Investigator Program (YIP) award, the NSF CAREER award, a 2020 Honorable Mention for the IEEE Robotics and Automation Letters Best Paper Award, three best conference paper awards, including the AIAA Guidance, Navigation, and Control Conference and AIAA InfoTech, and five best student paper awards. Prof. Chung is an Associate Editor of the IEEE Transactions on Automatic Control and the AIAA Journal of Guidance, Control, and Dynamics. He was an Associate Editor of the IEEE Transactions on Robotics, and the Guest Editor of a Special Section on Aerial Swarm Robotics published in the IEEE Transactions on Robotics.
Gianluca Furano received the Ph.D. in microelectronics engineering from University of Rome and since 2003 works for the European Space Agency’s Data System Division, Noordwijk, The Netherlands. He is in charge of research and development activities and he coordinates European Space Agency (ESA) activities on on-board artificial intelligence. He has authored or coauthored more than 100 publications. Among his interests in ESA are on-board data handling systems and their major components, such as space grade microprocessors and support electronics, meeting very stringent requirements in terms of radiation tolerance, reliability, availability, and safety; key avionics building blocks such as platform mass memories, remote terminal units, on-board buses, and data networks; and on-board and space to ground data communication protocols including protocol security aspects. He also provides support to European Standardization Consultative Committee for Space Data Systems (CCSDS) and European Cooperation for Space Standardization (ECSS) in areas such as telemetry, telecommand and on-board data, and wireless and monitoring control interfaces.
The University of Adelaide
University of Luxembourg
Stanford’s Space Rendezvous Lab
The University of Sydney
European Space Agency
University of Luxembourg