Considering the collision probability of Active Debris Removal missions

Lidtke, Aleksander A.; Lewis, Hugh G.; Armellín, Roberto; Urrutxua, Hodei

doi:10.1016/j.actaastro.2016.11.012

Cited by 9 publications

(5 citation statements)

References 17 publications

(27 reference statements)

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“…For example, an assessment of these methods showed that the net, space-based laser, and robotic arm methods appear to be the most promising [69]. While some of the ADR proposals are to remove single larger-sized debris objects, there are also proposals to remove more pieces to save on the mission costs [51], [70], but a more extended ADR mission will also increase the collision probability with the ADR mission itself [71]. There is also a proposal that suggests the repositioning of large debris objects from crowded regions to a relatively less crowded altitude with a smaller lifetime [42].…”

Section: B Active Debris Removal (Adr)mentioning

confidence: 99%

Orbital Debris Threat for Space Sustainability and Way Forward (Review Article)

Murtaza

Pirzada

et al. 2020

IEEE Access

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Over the past 60 years, satellite technology has demonstrated its usefulness successfully. However, this usefulness is at stake from a future point of view, due to the well-admitted orbital/space debris threat. This article thoroughly reviews all aspects of space debris issue including causes, amount and sizes of orbital debris, potential threats, counter-strategies with their latest status and related legal issues to highlight the criticality and urgency of the problem. This review elaborates the fact that despite all the worries and threats, the efforts to confront this challenge are considerably insufficient until today. This bitter reality demands for at-least curtailing the number of future launches to ensure the long-term sustainability of space, until the improvement in debris situation. However, contradictory to this necessity, large satellite constellations have been proposed that can drastically increase the existing orbital population in coming years. This approach will certainly not help in improving the space environment in the future; instead, it can worsen the space environment situation as recent studies shows. Also, space resources (i.e. orbital slots and frequencies) are limited to accommodate many more satellite projects from commercial and government organization in the future. So, there is a serious question of how the space industry can move forward to maintain a balance in controlling the future number of the satellite while accommodating many commercial or government space entities. This article also identifies two optimized approaches as a way forward for future satellite projects that can also enhance the effectiveness of space technology in the future.

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Section: B Active Debris Removal (Adr)mentioning

confidence: 99%

Orbital Debris Threat for Space Sustainability and Way Forward (Review Article)

Murtaza

Pirzada

et al. 2020

IEEE Access

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“…The reward function g (•) reflects the threat of one particular debris. Some debris priority models focus on evaluating the thread of debris [39]- [41]. However, to evaluate the RL model and method in this paper, the reward function is only a performance indicator, so it is assumed to be the number of removed debris for validation.…”

Section: A Mission Descriptionmentioning

confidence: 99%

“…The best solution output is [1,30,39,19,59], which means the removal debris sequence is (1,3,4,2,6), and the removal time duration sequence is (1,22,19,19,19). The Q value of W/N also means the average reward, it is 5690/1500=3.7933 on the root node, and other Q values along the solution are shown in Table 4.…”

Section: Tests On Debris Set #1mentioning

confidence: 99%

A Reinforcement Learning Scheme for Active Multi-Debris Removal Mission Planning With Modified Upper Confidence Bound Tree Search

Yang

Hou

et al. 2020

IEEE Access

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The increasing number of space debris is a critical impact on space environment. Active multi-debris removal (ADR) mission planning technique with maximal reward objective is getting more attention. As the goal of Reinforcement Learning (RL) is in accordance with maximal-reward optimization model of ADR, the planning will be more efficient with the advanced RL scheme and RL algorithm. In this paper, first, an RL formulation is presented for the ADR mission planning problem. All the basic components of maximal-reward optimization model are recast in RL scheme. Second, a modified Upper Confidence bound Tree (UCT) search algorithm for the ADR planning task is developed, which both leverages the neural-network-assisted selection and expansion procedures for a better exploration and uses roll-out simulation in the backup procedure for robust value estimation. This algorithm fits the RL scheme of ADR mission planning and better balances the exploration and exploitation. Experimental comparison using three subsets of Iridium 33 debris cloud data reveals a better performance of this modified UCT over previously reported results and close UCT variants. INDEX TERMS Monte Carlo tree search, multi-debris active removal, reinforcement learning, space mission planning

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“…By the end of January 2021, the total weight of space debris had reached 8400 tons, with 128 million debris with a size of 0.1-1 cm, about 90,000 debris with a size of 1-10 cm and 34,000 debris with a size greater than 10 cm [1]. The has been a rapid increase in the amount of space debris and the increasingly serious space debris environment poses a serious challenge to the sustainable development of space activities [2][3][4][5][6][7]. Active removal of space debris has become a common consensus [8].…”

Section: Introductionmentioning

confidence: 99%

Energy Analysis of a Space-Energy Driven Laser-Ablation Debris Removal System

Yang

Shao

et al. 2022

Sustainability

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Space-energy driven laser-ablation debris removal is a feasible way to address the worsening space debris environment. Energy analysis is crucial for the design and run of a space-energy driven laser-ablation debris removal system. This study details the energy analysis of a space-energy driven laser-ablation debris removal system as affected by laser energy, frequency and range. The results show that the laser irradiation time and energy efficiency are decreased with increases in the laser energy and frequency, and the energy efficiency in the case of different planes is significantly lower than that in the case of coplanar. However, laser range has no effect on the perigee changing and energy efficiency. The results can effectively guide the removal scheme design and evaluation.

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Considering the collision probability of Active Debris Removal missions

Cited by 9 publications

References 17 publications

Orbital Debris Threat for Space Sustainability and Way Forward (Review Article)

Orbital Debris Threat for Space Sustainability and Way Forward (Review Article)

A Reinforcement Learning Scheme for Active Multi-Debris Removal Mission Planning With Modified Upper Confidence Bound Tree Search

Energy Analysis of a Space-Energy Driven Laser-Ablation Debris Removal System

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