STATE OF THE ART AND CHALLENGES IN THE STUDY OF THE USE OF SWARM TECHNOLOGY TO CONTROL THE RELATIVE MOTION OF ON-ORBIT SERVICE OBJECTS

Анотація

In modern astronautics, alongside with the traditional mission paradigm based on monolithic spacecraft, an alternative approach utilizing swarm space systems is emerging. This approach employs simpler, low-cost robotic spacecraft (agents) that work collectively to accomplish the mission objectives. The primary advantages of swarm technologies include system flexibility and adaptability to a wide range of operational scenarios. However, approaches to the deployment and control of such multi-agent groups (e.g., nanosatellites) remain insufficiently developed. On the other hand, research is underway on improving relative motion estimation and control methods for on-orbit service targets, especially uncooperative and/or unknown ones and methods to control their motion. This is due to the fact that a service operation should usually be preceded by damping the target's relative angular motion. Several studies have highlighted the critical role of spacecraft swarms in on-orbit service applications.

The goal of this study is to analyze the state of the art in research on the use of swarm technology to control the relative motion of on-orbit service targets and identify challenges in swarm technology implementation, including those that can be resolved using previous studies conducted at the Institute of Technical Mechanics of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine. Publications on the use of swarm technology in space missions are overviewed. Based thereon, the study identifies stages of the problem of on-orbit service target motion control using swarm systems and assesses the problem resolution degree at each stage: encapsulation, capture, inertial and motion parameter identification, and relative motion control. The main challenges in swarm-based target control are identified, and ways to resolve them are outlined.

Swarm behavior at the capture stage seems to be least investigated. Unlike the encapsulation stage, the approach based on the behavior of natural systems is not fully suitable for capture due to its implementation complexity and inability to minimize energy consumption. In the authors’ opinion, the approach should be extended to include time-shared control principles, thus allowing the agents to attach to the target one by one, each to the nearest attachment point at an appropriate time.

The practical significance of this study lies in identifying the key challenges in the use of swarm technology for relative motion control in on-orbit service, thus furthering their resolution.  

REFERENCES

1. Asri E. G., Zhu Z. H. An introductory review of swarm technology for spacecraft on-orbit servicing. International Journal of Mechanical System Dynamics. 2024. V. 4. Pp. 3-21.
https://doi.org/10.1002/msd2.12098

2. Chang H., Huang P., Lu Z., Meng Z., Liu Z., Zhang Y. Cellular space robot and its interactive model identification for spacecraft takeover control. International Conference on Intelligent Robots and Systems (IROS) (Daejeon, Korea, 2016). 2016. Pp. 3069-3074.
https://doi.org/10.1109/IROS.2016.7759475

3. Chang H., Huang P., Lu Z., Meng Z., Liu Z., Zhang Y. Inertia parameters identification for cellular space robot through interaction. Aerospace Science and Technology. 2017. V. 71. Pp. 464-474.
https://doi.org/10.1016/j.ast.2017.09.044

4. Golovko M. G., Bezuglyi V. A., Bondarenko S. G., Rubakha Yu. A., Pokrovskii R. O. Technical aspects of space debris control. Ecology and Noospherology. 2012. V. 23. No. 1-2. Pp. 110-120. (In Russian).

5. Fokov O. A., Savchuk A. P. Algorithms of the operation of a self-contained system for slowing down the rotation of a non-cooperative object of on-orbit servicing. Teh. Meh. 2019. No. 4. Pp. 44-58. (In Russian). https://doi.org/10.15407/itm2019.04.044

6. Fokov O. A. Pose change determination method for an on-orbit service object with an unknown shape. Teh. Meh. 2024. No. 3. Pp. 35-48. (In Ukrainian).
https://doi.org/10.15407/itm2024.03.035

7. Huang H., Yang L., Zhu Y., Zhang Y. Collective trajectory planning for satellite swarm using inter-satellite electromagnetic force. Acta Astronautica. 2014. V. 104, No. 1. Pp. 220-230.
https://doi.org/10.1016/j.actaastro.2014.07.032

8. Scharf D. P., Hadaegh F. Y., Ploen S. R. A survey of spacecraft formation flying guidance and control (part II): control. Proceedings of the American Control Conference. 2004. V. 4. Pp. 2976-2985.
https://doi.org/10.23919/ACC.2004.1384365

9. Suzuki M., Uchiyama K., Bennet D. J., McInnes C. R. Three-dimensional formation flying using bifurcating potential fields. AIAA Guidance, Navigation, and Control Conference (Chicago, Illinois, 10-13 August 2009). AIAA 2009-5884. https://doi.org/10.2514/6.2009-5884

10. Asri E. G., Zhu Z. H. Bioinspired consensus-based spacecraft swarm control for autonomous capture of uncooperative targets. Acta Astronautica. 2025. V. 234. Pp. 419-428.
https://doi.org/10.1016/j.actaastro.2025.05.009

11. Sabatini M., Palmerini G. B. Collective control of spacecraft swarms for space exploration. Celestial Mechanics and Dynamical Astronomy. 2009. V. 105. Pp. 229-244.
https://doi.org/10.1007/s10569-009-9183-8

12. Zhang Z., Zhu Z. H., Zhang D. Behavior-inspired event-triggered control of spacecraft swarms for autonomous capture of uncooperative targets. Engineering. 2026. 30 pp.
https://doi.org/10.1016/j.eng.2026.04.014

13. Sabatini M. Autonomous control of satellite swarms using minimal vision-based behavioral control. Aerospace. 2026. V. 13. No. 3. Art. 207. https://doi.org/10.3390/aerospace13030207

14. D'Amico S. Autonomous Formation Flying in Low Earth Orbit : Ph.D. Thesis / Technical University of Delft. Delft, The Netherlands, March 2010. URL: https://www.researchgate.net/publication/224993195_Autonomous_Formation_Flying_in_Low_Earth_Orbit (Last accessed on August 12, 2026).

15. An M., Wang Z., Zhang Y. Self-organizing control strategy for asteroid intelligent detection swarm based on attraction and repulsion. Acta Astronautica. 2017. V. 130. Pp. 84-96.
https://doi.org/10.1016/j.actaastro.2016.10.038

16. Savchuk A. P., Fokov O. A. Non-cooperative object parameter determination in orbital service tasks. Teh. Meh. 2018. No. 4. Pp. 30-45. (In Russian).
https://doi.org/10.15407/itm2018.04.030

17. Lichter M. D., Dubowsky S. Estimation of state, shape, and inertial parameters of space objects from sequences of range images. Proc. SPIE 5267, Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision (30 Sept 2003). 2003. V. 5267. Pp. 194-205.
https://doi.org/10.1117/12.514813

18. Tweddle B. E., Saenz-Otero A., Leonard J. J., Miller D. W. Factor graph modeling of rigid-body dynamics for localization, mapping, and parameter estimation of a spinning object in space. Journal of Field Robotics. 2015. V. 32. No. 6. Pp. 897-933. https://doi.org/10.1002/rob.21548

19. Setterfield T. P., Miller D. W., Saenz-Otero A., Frazzoli E., Leonard J. J. Inertial properties estimation of a passive on-orbit object using polhode analysis. Journal of Guidance, Control, and Dynamics. 2018. V. 41. No. 10. Pp. 2214-2231. https://doi.org/10.2514/1.G003394

20. Matsuka K., Santamaria-Navarro A., Capuano V., Harvard A., Rahmani A., Chung S.-J. Collaborative pose estimation of an unknown target using multiple spacecraft. IEEE Aerospace Conference (Big Sky, MT, USA, 2021). 2021. Pp. 1-11.
https://doi.org/10.1109/AERO50100.2021.9438352

21. Meng Q., Han D., Wang Z. A model-free method for attitude estimation and inertial parameter identification of a noncooperative target. Advances in Space Research. 2023. V. 71. Iss. 3. Pp. 1735-1751. https://doi.org/10.1016/j.asr.2022.09.029

22. An Q., Yuan Y., Liu H., Yue X. Space-based visual localization and 3D reconstruction of unknown orbital target with observability analyses on a ROS/Gazebo-based framework. Chinese Journal of Aeronautics. 2026. Art. 104202. https://doi.org/10.1016/j.cja.2026.104202

23. Nocerino A., Fasano G., Grassi M., Opromolla R. LIDAR-based relative navigation and 3d target reconstruction for close proximity operations with unknown target. AIAA SCITECH 2026 Forum (8 Jan 2026). 2026. AIAA 2026-2260. https://doi.org/10.2514/6.2026-2260

24. Morgan D., Subramanian G. P., Chung S.-J., Hadaegh F. Y. Swarm assignment and trajectory optimization using variable-swarm, distributed auction assignment and sequential convex programming. The International Journal of Robotics Research. 2016. V. 35. Iss. 10. Pp. 1261-1285.
https://doi.org/10.1177/0278364916632065

25. Spenko M. Making contact: a review of robotic attachment mechanisms for extraterrestrial applications. Advanced Intelligent Systems. 2023. V. 5. No. 3. Art. 2100063.
https://doi.org/10.1002/aisy.202100063

26. Estrada M. A., Hockman B., Bylard A., Hawkes E. W., Cutkosky M. R., Pavone M. Free-flyer acquisition of spinning objects with gecko-inspired adhesives. IEEE International Conference on Robotics and Automation (ICRA) (Stockholm, Sweden, May 16-21, 2016). 2016. Pp. 4907-4913.
https://doi.org/10.1109/ICRA.2016.7487696

27. Hawkes E. W., Jiang H., Christensen D. L., Han A. K., Cutkosky M. R. Grasping without squeezing: design and modeling of shear-activated grippers. IEEE Transactions on Robotics. 2018. V. 34. No. 2. Pp. 303-316. https://doi.org/10.1109/TRO.2017.2776312

28. Jiang H., Hawkes E. W., Fuller C., Estrada M. A., Suresh S. A., Abcouwer N., Han A. K., Wang S., Ploch C. J., Parness A., Cutkosky M. R. A robotic device using gecko-inspired adhesives can grasp and manipulate large objects in microgravity. Science Robotics. 2017. V. 2. No. 7. 11 pp.
https://doi.org/10.1126/scirobotics.aan4545

29. Chen T. G., Cauligi A., Suresh S. A., Pavone M., Cutkosky M. Testing gecko-inspired adhesives with Astrobee aboard the International Space Station: readying the technology for space. IEEE Robotics & Automation Magazine. 2022. V. 29. No. 3. Pp. 24-33.
https://doi.org/10.1109/MRA.2022.3175597

30. Zhu M., Zhang Y., Chen X. Contact and capture dynamics analysis of a biomimetic dry adhesion-based grasping mechanism. Journal of Physics: Conference Series. 2025. Vol. 3109. No. 1. Art. 012061. https://doi.org/10.1088/1742-6596/3109/1/012061

31. Alpatov A. P. Time-Shared Control of Mechanical Systems. Kyiv: Naukova Dumka, 1998. 245 pp. (In Russian).

32. Zhai K., Wang T., Meng D. Optimal excitation design for identifying inertia parameters of spacecraft. Acta Astronautica. 2017. V. 140. Pp. 370-379.
https://doi.org/10.1016/j.actaastro.2017.08.002

33. Han N., Luo J., Ma W., Yuan J. Integrated identification and control for nanosatellites reclaiming failed satellite. Acta Astronautica. 2018. V. 146. Pp. 387-398.
https://doi.org/10.1016/j.actaastro.2018.03.006

34. Fan S., Xing F., Liu X., Chen X., You Z. Quick-response attitude takeover control using multiple servicing spacecraft based on inertia properties identification. Advances in Space Research. 2022. V. 70. No. 7. Pp. 1890-1916. https://doi.org/10.1016/j.asr.2022.06.049