Zero-G Lab: A multi-purpose facility for emulating space operations

Olivares-Mendez, Miguel; Makhdoomi, Mohatashem Reyaz; Yalçın, Barış Can; Bokal, Zhanna; Muralidharan, Vivek; Ortiz Del Castillo, Miguel; Gaudilliere, Vincent; Pauly, Leo; Borgue, Olivia; Alandihallaj, Mohammadamin; Thoemel, Jan; Skrzypczyk, Ernest; Rathinam, Arunkumar; Barad, Kuldeep Rambhai; Shabayek, Abd El Rahman; Hein, Andreas M.; Aouada, Djamila; Martinez, Carol

doi:10.1016/j.jsse.2023.09.003

Cited by 8 publications

(2 citation statements)

References 14 publications

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“…The adaptive control strategy significantly extended VI. FUTURE STUDIES Future studies will include the experimental validation and verification of the proposed controller using FlexeS in Zero-G Lab of SnT, University of Luxembourg [38]. The proposed controller will be integrated to ROS (Robot Operating System) infrastructure of Zero-G Lab.…”

Section: Discussionmentioning

confidence: 99%

Adaptive Control Scheme for Space Debris Capture in the Presence of Mass and Inertia Uncertainty

Christidi-Loumpasefski,

Yalçın,

Delisle

et al. 2024

IEEE Access

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This paper proposes an adaptive control scheme for capturing uncooperative space debris having uncertain inertial parameters. Debris parameters may be unknown or uncertain due to limited data or changes in orbit due to collisions. To address this challenge, the proposed scheme integrates an inertial parameter identification law with the impedance control strategy of FlexeS (Flexible Capture System). During the pre-capture phase, motion data is utilized to identify the debris' center of mass (CM), leading to the optimal capture point that minimizes impact moments. During contact, the impedance-controlled actuator(s) is(are) activated while the scheme concurrently provides accurate estimates of the debris mass and inertia, enabling the updating of controller gains and thus ensuring sufficient contact time for successful capture. Hence, the proposed adaptive scheme allows FlexeS to handle the debris parameter uncertainties. The simulation study demonstrates the scheme's effectiveness and necessity. The performance of the proposed adaptive scheme is compared with a non-adaptive scheme. The results affirm the superiority of the adaptive scheme in achieving successful soft capture of uncooperative debris in the presence of mass and inertia uncertainties and highlight its potential for future space debris mitigation missions.

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Section: Discussionmentioning

confidence: 99%

Adaptive Control Scheme for Space Debris Capture in the Presence of Mass and Inertia Uncertainty

Christidi-Loumpasefski,

Yalçın,

Delisle

et al. 2024

IEEE Access

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“…In 2019, the Interdisciplinary Center of Security, Reliability and Trust (SnT) at University of Luxembourg undertook the project of developing the "SnT Zero-G Lab," a facility for mimicking space environment and simulating rendezvous-related processes [18][19][20][21]. During the development, SnT Zero-G Lab had faced cost and schedule challenges related to the lack of literature documenting the development of such facilities.…”

Section: Introductionmentioning

confidence: 99%

Lessons from a Space Lab: An Image Acquisition Perspective

Pauly,

Jamrozik,

del Castillo

et al. 2023

International Journal of Aerospace Engineering

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The use of deep learning (DL) algorithms has improved the performance of vision-based space applications in recent years. However, generating large amounts of annotated data for training these DL algorithms has proven challenging. While synthetically generated images can be used, the DL models trained on synthetic data are often susceptible to performance degradation when tested in real-world environments. In this context, the Interdisciplinary Center of Security, Reliability and Trust (SnT) at the University of Luxembourg has developed the “SnT Zero-G Lab,” for training and validating vision-based space algorithms in conditions emulating real-world space environments. An important aspect of the SnT Zero-G Lab development was the equipment selection. From the lessons learned during the lab development, this article presents a systematic approach combining market survey and experimental analyses for equipment selection. In particular, the article focuses on the image acquisition equipment in a space lab: background materials, cameras, and illumination lamps. The results from the experiment analyses show that the market survey complimented by experimental analyses is required for effective equipment selection in a space lab development project.

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On-ground validation of orbital GNC: Visual navigation assessment in robotic testbed facility

Muralidharan,

Makhdoomi,

Žinys

et al. 2024

Astrodyn

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CubeSats have become versatile platforms for various space missions (e.g., on-orbit servicing and debris removal) owing to their low cost and flexibility. Many space tasks involve proximity operations that require precise guidance, navigation, and control (GNC) algorithms. Vision-based navigation is attracting interest for such operations. However, extreme lighting conditions in space challenge optical techniques. The on-ground validation of such navigation systems for orbital GNC becomes crucial to ensure their reliability during space operations. These systems undergo rigorous testing within their anticipated operational parameters, including the exploration of potential edge cases. The ability of GNC algorithms to function effectively under extreme space conditions that exceed anticipated scenarios is crucial, particularly in space missions where the scope of errors is negligible. This paper presents the ground validation of a GNC algorithm designed for autonomous satellite rendezvous by leveraging hardware-in-the-loop experiments. This study focuses on two key areas. First, the rationale underlying the augmentation of the robot workspace (six-degree-of-freedom UR10e robot + linear rail) is investigated to emulate relatively longer trajectories with complete position and orientation states. Second, the control algorithm is assessed in response to uncertain pose observations from a vision-based navigation system. The results indicate increased control costs with uncertain navigation and exemplify the importance of on-ground testing for system validation before launch, particularly in extreme cases that are typically difficult to assess using software-based testing.

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Zero-G Lab: A multi-purpose facility for emulating space operations

Cited by 8 publications

References 14 publications

Adaptive Control Scheme for Space Debris Capture in the Presence of Mass and Inertia Uncertainty

Adaptive Control Scheme for Space Debris Capture in the Presence of Mass and Inertia Uncertainty

Lessons from a Space Lab: An Image Acquisition Perspective

On-ground validation of orbital GNC: Visual navigation assessment in robotic testbed facility

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