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Space debris is growing dramatically with the rapid pace of human exploration of space, which seriously threaten the safety of artificial spacecraft in orbit. Therefore, the active debris removal (ADR) is important. This review aims to review the ADR methods and to advance related research in the future. The current research and development status...
Citations
... Different types of space deployable masts can be selected on the basis of particular mis sion requirements [4][5][6][7]. The deployable mast can be adapted to the volume restriction of the launcher in the folded state and can bear the extreme loads that the mechanism in the deployed state cannot withstand during the launching process [8]. More over, the telescopic tubular mast (TTM) is an outstanding rep resentative of the space deployable mast, which is much stiffer, more stable, and more precise than others in orbit [9]. ...
Space deployable masts, as one of the most widely used branches of space deployable structures, can provide driving, positioning, and transmission functions for spacecraft in orbit, which are irreplaceable in complex space activities. The nonmagnetic telescopic tubular mast (NMTTM) is designed and manufactured by the Shenyang Institute of Automation, Chinese Academy of Sciences, aboard the SATech-01 satellite to keep the magnetic probe assembly away from magnetic interference and realize global magnetic field measurement. The NMTTM can withstand complicated vibration and shock during rocket launching in the retracted state of 0.95 m, while it can be stably released and deployed to 5.28 m in orbit. NMTTM was successfully launched into Sun-synchronous orbit on 27 July 2022, fully deployed, and generated the positioning signal after a duration of 19 min and 16 s for the deployment process on 7 November. This paper focuses on the whole process of NMTTM from mission requirements to structure design and manufacture, through to releasing, deployment, and locking technology, environmental simulation tests, up to on-orbit deployment verification, which provides valuable experience for the subsequent development and application of large-scale space deployable masts.
... To delay or prevent the rapid onset of the Kessler syndrome, many space debris removal methods have been proposed and investigated [10], ranging from capture methods for large debris objects [11][12][13][14][15][16][17][18] over passive methods to accelerate natural decay [19][20][21][22][23][24] to propulsion-based approaches [25][26][27][28][29][30][31][32][33], including applicability to small-size debris. Most of the literature focuses on the removal of large debris objects and prevention of break-up events, with less attention towards handling the consequence of such events. ...
As artificial objects in Low Earth Orbit (LEO) become more numerous, the risk for breakup events threatening space-based services increases rapidly. Laser ablation methods have previously been proposed for the removal of small-size (1 - 10
cm) debris fragments, but a mission-level feasibility study is yet to be performed. This work investigates the mission concept and spacecraft design feasibility of a space-based laser aiming to de-orbit 50% of the debris generated by an on-orbit catastrophic event, using an agent-based modelling approach applied to the 2009 Cosmos-Iridium collision example. Several parameters were varied to generate a feasibility envelope on the payload performance, showing that the necessary capabilities for mission feasibility are within ranges achievable with current or near-term technology. Additionally, the financial challenges of the mission are discussed. A cost estimate for a single-flight mission of 550 M€ was generated based on the conceptual design developed for this study and is in agreement with previous
research. This work shows that a laser ablation concept for the removal of small-size debris in LEO is feasible both technically and financially. It further provides a modelling base for future research on similar concepts for different mission scenarios.
... The space community recognizes the urgency of this issue and is actively exploring solutions for debris mitigation. Research in this area focuses on a variety of proactive methods, such as net capture, tethering, direct capture, and harpoon-based strategies [4], [5]. Among the various strategies being researched, the direct capture technique is emerging as a particularly promising approach. ...
Capturing space debris forms the foundation for both on-orbit servicing and the removal of space debris. The challenge in this process arises from the absence of stable anchoring points and the unpredictability of motion parameters, rendering conventional spacecraft manipulator techniques unsuitable for space debris capture. In this research, we have created a method rooted in deep reinforcement learning to tackle the intricate challenge of robotic gripping, informed by tactile sensor data. Rather than manually crafting features, deep learning affords us the ability to simplify the task, fostering a learning environment for the robot to adapt grasping strategies through a process of experimentation. Our procedure implements an off-policy reinforcement learning architecture, utilizing the advanced algorithms to optimize the robotic gripper's capacity to handle objects not fixed in space, focusing on enhancing the fine grasp success rate. To efficiently master the gripping task, we have formulated a distinct reward function that delivers precise and meaningful feedback to the learning agent. Our system is trained completely within a simulated setting provided by the PyBullet environment, eliminating the need for demonstrations or pre-existing task knowledge. For this study, we examine a scenario where a Robotiq 3-Finger gripper is required to navigate toward a floating object, pursue it, and ultimately secure it. By conducting agent training within a simulated environment, we can test a variety of situations and conditions, equipping the agent with a resilient and adaptable gripping policy.
... Additionally, the increasing amount of space debris can also hinder the efficiency and feasibility of future space missions, potentially blocking access to certain orbits or making satellite launches more complex. Multiple active space debris removal techniques are currently under investigation by researchers, including net capture, tethers, direct capture, and harpoon mechanisms [1][2][3][4]. Direct capture techniques employ robotic arms, equipped with computer vision and tactile sensors, to extend and secure space debris. By merging these technologies and sensors, the robot can precisely align with the rotational speeds of the targeted debris, gently secure it, and then apply a propulsive force to guide it out of orbit. ...
The focus of this research is the creation of a deep reinforcement learning approach to tackle the challenging task of robotic gripping through tactile sensor data feedback. Leveraging deep reinforcement learning, we have sidestepped the necessity to design features manually, which simplifies the issue and allows the robot to acquire gripping strategies via trial-and-error learning. Our technique utilizes an off-policy reinforcement learning model, integrating deep deterministic policy gradient structure and twin delayed attributes to facilitate maximum precision in gripping floating items. We have formulated a comprehensive reward function to provide the agent with precise, insightful feedback to facilitate the learning of the gripping task. The training of our model was executed solely in a simulated environment using the PyBullet framework and did not require demonstrations or pre-existing knowledge of the task. We examined a gripping task with a 3-finger Robotiq gripper for a case study, where the gripper had to approach a floating object, pursue it, and eventually grip it. This training methodology in a simulated setting allowed us to experiment with various scenarios and conditions, thereby enabling the agent to develop a resilient and adaptable grip policy.
... In fact, experts are indicating that the current situation is already showing a growing trend in the number of in-orbit collisions and number of resident objects even for "no further launches" scenario [6,7]. The sustainability of the space environment is, therefore, under scrutiny by the scientific community [8]: mitigation techniques [9][10][11] and strategies to reduce the hazard of space debris [12][13][14] are under evaluation by all the main stakeholders [15,16]. In addition, it is still crucial to understand the physical processes involved in spacecraft collisions and fragmentations and how these events can affect the space environment [17] and other spacecraft [18]. ...
In the next years, the space debris population is expected to progressively grow due to in-space collisions and break-up events; in addition, anti-satellite tests can further affect the debris environment by generating large clouds of fragments. The simulation of these events allows identifying the main parameters affecting fragmentation and obtaining statistically accurate populations of generated debris, both above and below detection thresholds for ground-based observatories. Such information can be employed to improve current fragmentation models and to reproduce historical events to better understand their influence on the non-detectable space debris population. In addition, numerical simulation can also be used as input to identify the most critical objects to be removed to reduce the risk of irreversible orbit pollution. In this paper, the simulation of historical in-orbit fragmentation events is discussed and the generated debris populations are presented. The presented case-studies include the COSMOS-IRIDIUM collision, the COSMOS 1408 anti-satellite test, the 2022-151B CZ-6A in-orbit break-up, and a potential collision of ENVISAT with a spent rocket stage; for these events, results are presented in terms of cumulative fragments distributions and debris orbital distributions.
... Even at existing orbital debris levels, the risk of catastrophic chain reaction collisions, described as the Kessler effect [2], is hugely significant. Consequently, efforts are currently underway to develop debris removal and collision avoidance systems [3,4]. However, without the ability to accurately detect, track, and classify/identify space objects, attempts to "safely" remove or manage space debris, through whatever means, will ultimately fail. ...
The volume of space debris currently orbiting the Earth is reaching an unsustainable level at an accelerated pace. The detection, tracking, identification, and differentiation between orbit-defined, registered spacecraft, and rogue/inactive space ``objects'', is critical to asset protection. The primary objective of this work is to investigate the validity of Deep Neural Network (DNN) solutions to overcome the limitations and image artefacts most prevalent when captured with monocular cameras in the visible light spectrum. In this work, a hybrid UNet-ResNet34 Deep Learning (DL) architecture pre-trained on the ImageNet dataset, is developed. Image degradations addressed include blurring, exposure issues, poor contrast, and noise. The shortage of space-generated data suitable for supervised DL is also addressed. A visual comparison between the URes34P model developed in this work and the existing state of the art in deep learning image enhancement methods, relevant to images captured in space, is presented. Based upon visual inspection, it is determined that our UNet model is capable of correcting for space-related image degradations and merits further investigation to reduce its computational complexity.
... Handholds are often designed so that an astronaut always has a single hand in contact with the craft, thus tools should be designed for single-handed use where possible. Similarly, a line launcher could be used to deploy specialized sensors, intercept incoming objects, and secure components (Liu, Qiu, Li, & Yang, 2017;Zhao, Liu, & Wu, 2020;Sizov & Aslanov, 2020). Outside of the scope of handheld use, a space-based line launcher system could be mounted on a satellite as a capture or tether system (Sizov & Aslanov, 2020). ...
... For defense and industry, the use of optically ignited single-nozzle gyrojets with "soft rifling" could greatly reduce gun barrel corrosion in small arms (Kumar, Kalra, & Jha, 2022). In aerospace, similar units could be mounted on the bodies of spacecraft for object capture or antennae deployment (Sizov & Aslanov, 2020;Zhao, Liu, & Wu, 2020). The applications of the device are far too numerous to list, although certain limitations must be addressed. ...
Line launchers are devices that have been used for centuries for maritime rescue operations. The typical implementation is the use of a gun, rocket, or mechanical launcher to hurl a grappling hook or flotation buoy for stranded ships and overboard sailors. Microgravity offers analogous use cases, ranging from microsatellite operations to space debris interception. As such, the Lachesis line launcher is a handheld device that is purpose-built for microgravity applications. After the user pulls the trigger, a laser ignites a smoothbore rocket-propelled projectile which carries a nylon line behind it. Angled threads in the barrel provide the spin and stability that is typically only achieved by conventional rifling. To reduce weight, most components are 3D-printed out of polylactic acid (PLA), a biodegradable and light plastic. With a total weight of 68 g and a projectile kinetic energy of 0.127 J, the Lachesis line launcher presents an effective, potential option, even with contemporary operational constraints. The design combines several proven principles to demonstrate the viability and use case for an updated line launcher in orbital operations.
... This vicious circle is often referred to as the Kessler syndrome or collisional cascading [5,6]. There are multiple ways to prevent the situation from worsening, including proper spacecraft end-of-life management [7], active space debris removal [8,9], and improved operations to mitigate collision risk [4]. This study focuses on the latter aspect. ...
Spacecraft conjunction management plays a crucial role in the mitigation of space collisions. When a conjunction event occurs, resources and time are spent analyzing, planning, and potentially maneuvering the spacecraft. This work contributes to a subpart of the problem: Confidently identifying events that will not lead to a high collision probability, and therefore do not require further investigation. The method reduces the dimensionality of the data via principal component analysis (PCA) on a subset of features. High-risk regions are then determined by clustering the projected data, and events that do not belong to a high-risk cluster are pruned. A genetic algorithm (GA) is developed to optimize the number of clusters and feature selection of the model. Furthermore, an ensemble learning framework is proposed to combine the suboptimal models for better generalization. The results show that the first set of parameters pruned approximately 50% of the events in the testing set with no false negatives, whereas the second set of parameters pruned 70% of the events and maintained a near-perfect recall. These results could benefit the optimization of operational resources and allow operators to focus better on the events of interest.
... The space-net is considered as one of the most promising methods for debris removal, requiring the least knowledge about target object such as size, weight, and even angular rate of uncooperative object [15]. It allows a large capture range and does not require a specific attachment point on target, so more secure manipulation is possible [22,23]. Also, the space-net system, with lightweight and flexibility, can achieve better mission performance due to small launch masses and packaging volumes ( [24,25] , Fig. 3). ...
This paper conducts capture simulations using space-nets based on the spider-web structure for Korea’s first satellite, KITSAT-1 to investigate the capture performance of the spider-web space-net. A nonlinear structural dynamics analysis code, ABAQUS, is used in the simulation study. Explicit scheme is applied to represent the nonlinearity and geometrical large deformation behaviors of the space-net. The capture performance of two types of space-net is investigated when changing the design parameters of the space-net from the baseline model. The numerical results show that the spider-web space-net has a better capture performance than the square space-net, and the possibility of the space-net as a means of capturing KITSAT-1 is investigated.
... Consequently, the removal of space debris has emerged as a top priority in space missions (Space Foundation White Paper, 2020). Direct capture of objects is one approach for mitigating the issue, and it can be executed through rigid or flexible capture methods, as classified by Zhao et al., 2020. A variety of techniques for flexible direct capture, including harpoons, nets, and tentacles, have been suggested by Billot et al., 2014;Zhang and Huang, 2016;Forshaw et al., 2017. ...
In the past 2 decades, there has been increasing interest in autonomous multi-robot systems for space use. They can assemble space structures and provide services for other space assets. The utmost significance lies in the performance, stability, and robustness of these space operations. By considering system dynamics and constraints, the Model Predictive Control (MPC) framework optimizes performance. Unlike other methods, standard MPC can offer greater robustness due to its receding horizon nature. However, current literature on MPC application to space robotics primarily focuses on linear models, which is not suitable for highly non-linear multi-robot systems. Although Nonlinear MPC (NMPC) shows promise for free-floating space manipulators, current NMPC applications are limited to unconstrained non-linear systems and do not guarantee closed-loop stability. This paper introduces a novel approach to NMPC using the concept of passivity to multi-robot systems for space applications. By utilizing a passivity-based state constraint and a terminal storage function, the proposed PNMPC scheme ensures closed-loop stability and a superior performance. Therefore, this approach offers an alternative method to the control Lyapunov function for control of non-linear multi-robot space systems and applications, as stability and passivity exhibit a close relationship. Finally, this paper demonstrates that the benefits of passivity-based concepts and NMPC can be combined into a single NMPC scheme that maintains the advantages of each, including closed-loop stability through passivity and good performance through one-line optimization in NMPC.
