PRE2018 4 Group9: Difference between revisions

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== Group members ==
== Group members ====Who is doing what?==
Rob de Mooij 1017797<br>
{| class="wikitable" | border="1" | style="border-collapse:collapse"
Ilja van Oort 1001232<br>
|-
Sara Tjon 1247050<br>
! Member
Thomas Pilaet 0999458<br>
! ID number
Joris Zandeberge 1231962<br>
|-
| Rob de Mooij
| 1017797
|-
| Ilja van Oort
| 1001232
|-
| Sara Tjon
| 1247050
|-
| Thomas Pilaet
| 0999458
|-
| Joris Zandeberge
| 1231962
|}


==Problem statement==
==Problem statement==

Revision as of 10:39, 5 May 2019

Group members ====Who is doing what?

Member ID number
Rob de Mooij 1017797
Ilja van Oort 1001232
Sara Tjon 1247050
Thomas Pilaet 0999458
Joris Zandeberge 1231962

Problem statement

The amount of collisions between satellites and space debris increases exponentially, due to the growing amount of space debris.
Chance that a satellite collides with a piece of debris bigger than 1 cm in a year:
2007: 17-20%, 2010: 50%
Consequences: no internet, no gps, costs a lot of money, space travel may become more difficult/impossible

Objectives

  • Analyzing the available methods to remove space debris
  • Find methods on how to prevent new space debris (governance)
  • Further develop a promising method


Users and their requirements

Users:

  • Satellite owners (governments, space associations)

Requirements:

  • re-usable
  • quick to implement
  • hard to abuse
  • versatile (for both smaller and larger debris)
  • autonomous
  • durable
  • affordable


Approach, milestone and deliverables

Approach:
Reading papers to get a good picture of the current problem and the state-of-the-art technology
Analyzing and comparing possible methods for space debris removal by looking at their pros and cons
Further development of a (combination of) promising technique(s) with a model or prototype.

Milestones:
Week 2: Determined subject; defined plan
Week 3: Find state of the art methods; finished literature search
Week 4: Determine promising method(s)
Week 5: Basic model
Week 6: Final model
Week 7: Results model, implement model in USE, finalized wiki
Week 8: Presentation

Deliverables

  • Wiki page
  • Presentation
  • Model/prototype

Who is doing what?

What Who
Literature study All
Literature analysis All
Modelling Rob/Ilja/Sara
Prototyping Rob/Ilja/Sara
Updating wiki All
Implementation USE Joris/Thomas
Visualizing data/results Joris/Thomas
Presentation Joris/Thomas

Summary 25 scientific articles

Dubanchet, V., Saussié, D., Alazard, D., Bérard, C., & Peuvédic, C. Le. (2015). Modeling and control of a space robot for active debris removal. CEAS Space Journal, 7(2), 203–218. https://doi.org/10.1007/s12567-015-0082-4
This paper focusses on the technical aspects of using a robotic arm on a ‘chaser’ satellite to capture large debris. This approach is considered to be the most realistic to actually be employed in the upcoming years. In the introduction, several efforts in achieving the modeling and control of such a system (in space) are outlined. In the second section, the main issues in achieving this are described. In the third and fourth section, an algorithm used to model and simulate the dynamics of this satellite and the method of controlling it are described. The resulting system is then simulated using Matlab (the code is provided in the paper).

Flegel, S., Krisko, P., Gelhaus, J., Wiedemann, C., Möckel, M., Vörsmann, P., … Matney, M. (2010). Modeling the Space Debris Environment with MASTER2009 and ORDEM2010. Proceedings of the 38th COSPAR Scientific Assembly, (January).
This paper describes and compares two software tools (MASTER-2009 and ORDEM2010 developed by ESA and NASA respectively) used to describe debris orbiting the earth. The main goal of these tools is to estimate the object flux onto a specified target object and is therefore useful in achieving safe space travel. In MASTER, debris is simulated based on lists of known historical events responsible for scattering debris in earth’s orbit. Results are also validated using historical telescope/radar data. ORDEM is designed to reliably estimate orbital debris flux on spacecraft using telescope or radar fields-of-view. Therefore, both programs make heavy use of empirical data for their predictions. Results of the program deviate particularly in debris with a size of 1 mm to 1 cm. These bits of debris are particularly difficult to model, as the amount of measurement data is very small. Reasons for the deviation of the results for these small debris are described in the paper.

Klinkrad, H. (2006). Space debris : models and risk analysis. Springer.
This book extensively covers space debris in general and describes the technical aspects of this debris in detail. In chapters 2 to 6, it is outlined how the space debris environment can be characterized and modelled using measurement data. Furthermore, it is explained how the future of space debris orbiting earth can be predicted and how this could be influenced by mitigation measures. Chapters 7 to 9 describe aspects of risk assessment and prevention within on-orbit shielding, collision avoidance and re-entry risk management. Chapter 10 gives an overview of the risks associated with natural meteoroids and meteorites. Lastly, chapter 11 overviews the importance of space debris research and international policy and standardization issues.
Understanding the causes and controlling its sources is essential to allow for safe space flight in the future. This can only be achieved through international cooperation. This has been done through international information exchange and international cooperation at a technical level. Furthermore, steps have already been taken in establishing space debris mitigation standards, guidelines, codes of conduct and policies by several space agencies, governmental bodies and international space operators.

Yazdkhasti, S., & Sasiadek, J. Z. (2017). Space Robot Relative Navigation for Debris Removal. IFAC-PapersOnLine, 50(1), 7929–7934. https://doi.org/10.1016/j.ifacol.2017.08.767
In order for a ‘chaser’ (spacecraft capable of removing space debris) to properly navigate towards its target, it must be able to estimate the pose and motion of the target. In the introduction, several works addressing this problem are outlined. This paper presents a method to estimate the relative position, linear and angular velocity and the attitude of space debris using vision measurements (using stereo cameras). In order to estimate the relative states between spacecraft, the Multiplicative Extended Kalman Filter and Unscented Kalman Filter were applied. The methodology is described by first outlining the coordinate systems used. Afterwards, the estimation algorithm is described (in which a set of feature points tracked by a stereo camera are key). Then, the described algorithms are validated using a simulation experiment. This paper could be very interesting for our model. Perhaps we could translate the presented algorithm into a script and further build on it.

Colmenarejo, P., Avilés, M., & di Sotto, E. (2015). Active debris removal GNC challenges over design and required ground validation. CEAS Space Journal, 7(2), 187–201. https://doi.org/10.1007/s12567-015-0088-y
In this paper, proposed techniques for active debris removal (ADR) are categorized as follows:
- Contactless techniques (e.g. an ion beam), which can mostly build on existing techniques as opposed to using new ones
- Techniques requiring rigid contact (e.g. through a robotic arm), in which de-orbiting can be achieved by directly transmitting a force/torque to the debris
- Techniques requiring non-rigid contact (e.g. using flexible tentacles), which can entail intricate dynamics
A list of the proposed techniques can be retrieved from table 1 in the paper. As of yet, the most technologically advanced methods are the use of a robotic arm and capture through a tethered net.
Additionally, the main operational phases of active debris removal are outlined:
1. Ground controlled phase: In this phase, the “chaser” is brought closer to the target, usually not autonomously.
2. Fine orbit synchronization phase: The chaser moves to the (approximate) orbit of the target, which can be autonomous or partially using ground support
3. Short range phase: the final (passive) approach toward the target. Challenges here (which we could also address) are:
- Necessity to determine debris angular velocity and shape using optical observation, which most likely requires image processing techniques
- Necessity to synchronize the chaser with the angular motion of the debris
- In case of contact, necessity to de-tumble/control the resulting composite satellite
4. Terminal approach/capture
5. De-orbiting
Clearly, the fourth and fifth phase are very specific to the technique chosen for debris removal. Furthermore, the following aspects are discussed in the paper in detail:
1. Terminal approach using visual-based navigation
2. Ground validation of guidance, navigation and control systems based on hardware-in-the-loop test facilities