Special Issue "Spacecraft Detection and Pose Estimation"
Deadline for manuscript submissions: 31 March 2024 | Viewed by 621
Interests: object detection; deep neural networks; pose estimation; non-cooperative targets; reinforcement learning
Interests: aerospace vehicle dynamics and control
Special Issues, Collections and Topics in MDPI journals
Special Issue in Drones: Perception, Decision-Making and Control of Intelligent Unmanned System
Special Issue in Aerospace: Deep Space Exploration
Spacecraft detection and pose estimation, i.e., the process of identifying and determining the position and orientation of spacecraft in space, is an important area of research in the field of aerospace engineering. Accurate pose estimation is critical for a variety of applications including communication, navigation, control, and spacecraft guidance, as well as scientific research, especially for on-orbit manipulation, spacecraft rescuing, and cleaning.
However, spacecraft targets are often small and distant, and the background is often complex and dynamic, with significant changes in illumination and the potential for occlusion. These factors can make detection challenging and can increase the likelihood of missed or false detections. Moreover, obtaining real spacecraft data can be challenging, and there may be significant domain gaps between the simulated data and real-world data, which can impact the performance of the model.
Designing an effective spacecraft detection and pose estimation algorithm that can adapt to complex environments and domain gaps is a challenging task. However, recent advances in computer vision offer promising solutions. The development of such an algorithm has great theoretical and practical value and can significantly improve the operation and management of spacecraft in space.
To explore this topic further, we are launching a Special Issue in the "Aerospace" journal on "Spacecraft Detection and Pose Estimation". We invite experts and scholars in related fields to submit high-quality research papers for publication.
All research reviews and papers related to spacecraft detection and pose estimation can be submitted, including (but not limited to) the following:
(1) Datasets and domain gaps for space tasks;
(2) Spacecraft detection and pose estimation;
(3) Visual navigation for spacecraft operations;
(4) Hardware for vision and learning in space;
(5) Approach for mitigating effect of space environment;
(6) Space debris monitoring and mitigation;
(7) Spacecraft tracking.
Dr. Yanfang Liu
Prof. Dr. Shuang Li
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- domain gap
- object detection
- pose estimation
- visual navigation
- visual tracking