A comprehensive survey of space robotic manipulators for on-orbit servicing
| dc.contributor.author | Alizadeh, Mohammad | |
| dc.contributor.author | Zhu, Zheng Hong | |
| dc.date.accessioned | 2026-06-25T00:45:41Z | |
| dc.date.available | 2026-06-25T00:45:41Z | |
| dc.date.issued | 2024-10-09 | |
| dc.description | © 2024 Alizadeh and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | |
| dc.description.abstract | On-Orbit Servicing (OOS) robots are transforming space exploration by enabling vital maintenance and repair of spacecraft directly in space. However, achieving precise and safe manipulation in microgravity necessitates overcoming significant challenges. This survey delves into four crucial areas essential for successful OOS manipulation: object state estimation, motion planning, and feedback control. Techniques from traditional vision to advanced X-ray and neural network methods are explored for object state estimation. Strategies for fuel-optimized trajectories, docking maneuvers, and collision avoidance are examined in motion planning. The survey also explores control methods for various scenarios, including cooperative manipulation and handling uncertainties, in feedback control. Additionally, this survey examines how Machine learning techniques can further propel OOS robots towards more complex and delicate tasks in space. | |
| dc.description.sponsorship | Natural Sciences and Engineering Research Council of Canada Discovery Grant (RGPIN-2024-06290) and Collaborative Research and Training Experience Program Grant - SMART-ART (555425-2021) | |
| dc.identifier.citation | Alizadeh M and Zhu ZH (2024) A comprehensive survey of space robotic manipulators for on-orbit servicing. Front. Robot. AI 11:1470950. doi: 10.3389/frobt.2024.1470950 | |
| dc.identifier.issn | 2296-9144 | |
| dc.identifier.uri | https://doi.org/10.3389/frobt.2024.1470950 | |
| dc.identifier.uri | https://hdl.handle.net/10315/43799 | |
| dc.language.iso | en | |
| dc.publisher | Frontiers Media | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | On-orbit servicing | |
| dc.subject | Space robots | |
| dc.subject | Robotic manipulator | |
| dc.subject | Motion planning | |
| dc.subject | Machine learning | |
| dc.subject | Pose estimation | |
| dc.subject | Control | |
| dc.title | A comprehensive survey of space robotic manipulators for on-orbit servicing | |
| dc.type | Article |