AI4Space Call for Papers

Website:
https://aiforspace.github.io/2024/

CVPR
June 2024. Seattle.

Call for Papers:
We solicit papers for AI4Space. Papers will be reviewed and accepted
papers will be published in the proceedings of CVPR
Workshops. Accepted papers will also be presented at the workshop, to
be co-located with CVPR 2024 in Seattle.

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.

Paper deadline: 1 March 2024

The workshop will also feature exciting Invited Seminars by Soon-Jo
Chung (Caltech and JPL) and Gianluca Furano (ESA).

More details:
https://aiforspace.github.io/2024/