Using infrared based relative navigation for active debris removal

A debris-free space environment is becoming a necessity for current and future missions and activities planned in the coming years. The only means of sustaining the orbital environment at a safe level for strategic orbits (in particular Sun Synchronous Orbits, SSO) in the long term is by carrying out Active Debris Removal (ADR) at the rate of a few removals per year. Infrared (IR) technology has been used for a long time in Earth Observations but its use for navigation and guidance has not been subject of research and technology development so far in Europe. The ATV-5 LIRIS experiment in 2014 carrying a Commercial-of-The-Shelf (COTS) infrared sensor was a first step in de-risking the use of IR technology for objects detection in space. In this context, Cranfield University, SODERN and ESA are collaborating on a research to investigate the potential of IR-based relative navigation for debris removal systems. This paper reports the findings and developments in this field till date and the contributions from the three partners in this research

Using infrared based relative navigation for active debris removal

A debris-free space environment is becoming a necessity for current and future missions and activities planned in the coming years. The only means of sustaining the orbital environment at a safe level for strategic orbits (in particular Sun Synchronous Orbits, SSO) in the long term is by carrying out Active Debris Removal (ADR) at the rate of a few removals per year. Infrared (IR) technology has been used for a long time in Earth Observations but its use for navigation and guidance has not been subject of research and technology development so far in Europe. The ATV-5 LIRIS experiment in 2014 carrying a Commercial-of-The-Shelf (COTS) infrared sensor was a first step in de-risking the use of IR technology for objects detection in space. In this context, Cranfield University, SODERN and ESA are collaborating on a research to investigate the potential of IR-based relative navigation for debris removal systems. This paper reports the findings and developments in this field till date and the contributions from the three partners in this research

Infrared based monocular relative navigation for active debris removal

In space, visual based relative navigation systems suffer from the harsh illumination conditions of the target (e.g. eclipse conditions, solar glare, etc.). In current Rendezvous and Docking (RvD) missions, most of these issues are addressed by advanced mission planning techniques (e.g strict manoeuvre timings). However, such planning would not always be feasible for Active Debris Removal (ADR) missions which have more unknowns. Fortunately, thermal infrared technology can operate under any lighting conditions and therefore has the potential to be exploited in the ADR scenario. In this context, this study investigates the benefits and the challenges of infrared based relative navigation. The infrared environment of ADR is very much different to that of terrestrial applications. This study proposes a methodology of modelling this environment in a computationally cost effective way to create a simulation environment in which the navigation solution can be tested. Through an intelligent classification of possible target surface coatings, the study is generalised to simulate the thermal environment of space debris in different orbit profiles. Through modelling various scenarios, the study also discusses the possible challenges of the infrared technology. In laboratory conditions, providing the thermal-vacuum environment of ADR, these theoretical findings were replicated. By use of this novel space debris set-up, the study investigates the behaviour of infrared cues extracted by different techniques and identifies the issue of short-lifespan features in the ADR scenarios. Based on these findings, the study suggests two different relative navigation methods based on the degree of target cooperativeness: partially cooperative targets, and uncooperative targets. Both algorithms provide the navigation solution with respect to an online reconstruction of the target. The method for partially cooperative targets provides a solution for smooth trajectories by exploiting the subsequent image tracks of features extracted from the first frame. The second algorithm is for uncooperative targets and exploits the target motion (e.g. tumbling) by formulating the problem in terms of a static target and a moving map (i.e. target structure) within a filtering framework. The optical flow information is related to the target motion derivatives and the target structure. A novel technique that uses the quality of the infrared cues to improve the algorithm performance is introduced. The problem of short measurement duration due to target tumbling motion is addressed by an innovative smart initialisation procedure. Both navigation solutions were tested in a number of different scenarios by using computer simulations and a specific laboratory set-up with real infrared camera. It is shown that these methods can perform well as the infrared-based navigation solutions using monocular cameras where knowledge relating to the infrared appearance of the target is limited

Design of an unmanned, reusable vehicle to de-orbit debris in Earth orbit

The space debris problem is becoming more important because as orbital missions increase, the amount of debris increases. It was the design team's objective to present alternative designs and a problem solution for a deorbiting vehicle that will alleviate the problem by reducing the amount of large debris in earth orbit. The design team was asked to design a reusable, unmanned vehicle to de-orbit debris in earth orbit. The design team will also construct a model to demonstrate the system configuration and key operating features. The alternative designs for the unmanned, reusable vehicle were developed in three stages: selection of project requirements and success criteria, formulation of a specification list, and the creation of alternatives that would satisfy the standards set forth by the design team and their sponsor. The design team selected a Chain and Bar Shot method for deorbiting debris in earth orbit. The De-orbiting Vehicle (DOV) uses the NASA Orbital Maneuvering Vehicle (OMV) as the propulsion and command modules with the deorbiting module attached to the front

Convex Optimization-Based Model Predictive Control for the Guidance of Active Debris Removal Transfers

Active debris removal (ADR) missions have garnered significant interest as means of mitigating collision risks in space. This work proposes a convex optimization-based model predictive control (MPC) approach to provide guidance for such missions. While convex optimization can obtain optimal solutions in polynomial time, it relies on the successive convexification of nonconvex dynamics, leading to inaccuracies. Here, the need for successive convexification is eliminated by using near-linear Generalized Equinoctial Orbital Elements (GEqOE) and by updating the reference trajectory through a new split-Edelbaum approach. The solution accuracy is then measured relative to a high-fidelity dynamics model, showing that the MPC-convex method can generate accurate solutions without iterations

Pose and Shape Reconstruction of a Noncooperative Spacecraft Using Camera and Range Measurements

Recent interest in on-orbit proximity operations has pushed towards the development of autonomous GNC strategies. In this sense, optical navigation enables a wide variety of possibilities as it can provide information not only about the kinematic state but also about the shape of the observed object. Various mission architectures have been either tested in space or studied on Earth. The present study deals with on-orbit relative pose and shape estimation with the use of a monocular camera and a distance sensor. The goal is to develop a filter which estimates an observed satellite's relative position, velocity, attitude, and angular velocity, along with its shape, with the measurements obtained by a camera and a distance sensor mounted on board a chaser which is on a relative trajectory around the target. The filter's efficiency is proved with a simulation on a virtual target object. The results of the simulation, even though relevant to a simplified scenario, show that the estimation process is successful and can be considered a promising strategy for a correct and safe docking maneuver

CEU Session #4 - Space Robotics for On-Orbit Servicing and Space Debris Removal

The next ten years will see an unprecedented increase in the number of spacecraft deployed in Earth orbit and the number of commercial ventures operating space assets. The large increase in the number of spacecraft and the large increase in the commercial value of space will lead to renewed interest in robotic on-orbit servicing (OOS) and active debris removal (ADR). The lecture will provide a brief overview over the history of crewed and robotic OOS and discuss the missions planned for the near future. It will then proceed to identify the critical enabling technologies for a future, operational OOS and ADR infrastructure, discuss the technical challenges and present promising concepts and demonstrated technologies that can make routine OOS and ADR a possibility. The focus will be on robotics technologies and spacecraft guidance, navigation and control systems

Convex Optimization-based Model Predictive Control for Active Space Debris Removal Mission Guidance

A convex optimization-based model predictive control (MPC) algorithm for the guidance of active debris removal (ADR) missions is proposed in this work. A high-accuracy reference for the convex optimization is obtained through a split-Edelbaum approach that takes the effects of J2, drag, and eclipses into account. When the spacecraft deviates significantly from the reference trajectory, a new reference is calculated through the same method to reach the target debris. When required, phasing is integrated into the transfer. During the mission, the phase of the spacecraft is adjusted to match that of the target debris at the end of the transfer by introducing intermediate waiting times. The robustness of the guidance scheme is tested in a high-fidelity dynamical model that includes thrust errors and misthrust events. The guidance algorithm performs well without requiring successive convex iterations. Monte-Carlo simulations are conducted to analyze the impact of these thrust uncertainties on the guidance. Simulation results show that the proposed convex-MPC approach can ensure that the spacecraft can reach its target despite significant uncertainties and long-duration misthrust events.Comment: 39 pages, 16 figures. arXiv admin note: text overlap with arXiv:2308.0878

Robotics and AI-Enabled On-Orbit Operations With Future Generation of Small Satellites

The low-cost and short-lead time of small satellites has led to their use in science-based missions, earth observation, and interplanetary missions. Today, they are also key instruments in orchestrating technological demonstrations for On-Orbit Operations (O 3 ) such as inspection and spacecraft servicing with planned roles in active debris removal and on-orbit assembly. This paper provides an overview of the robotics and autonomous systems (RASs) technologies that enable robotic O 3 on smallsat platforms. Major RAS topics such as sensing & perception, guidance, navigation & control (GN&C) microgravity mobility and mobile manipulation, and autonomy are discussed from the perspective of relevant past and planned missions

FPGA-based multi-sensor relative navigation in space: Preliminary analysis in the framework of the I3DS H2020 project

The Horizon 2020 Integrated 3D Sensors (I3DS) project brings together the following entities throughout Europe: THALES ALENIA SPACE - France / Italy / UK / Spain, SINTEF (Norway), TERMA (Denmark), COSINE (Netherlands), PIAP Space (Poland), HERTZ Systems (Poland), and Cranfield University (UK). I3DS is co-funded under the Horizon 2020 EU research and development program and is part of the Strategic Research Cluster on Space Robotics Technologies. The ambition of I3DS is to produce a standardised modular Inspector Sensor Suite (INSES) for autonomous orbital and planetary applications for future space missions. Orbital applications encompass activities such as on-orbit servicing and repair, space rendezvous and docking, collision avoidance and active debris removal (ADR). Simultaneous localisation and surface mapping (SLAM) for planetary exploration and general navigation in an unknown environment for scientific purposes can be considered in planetary applications. These envisaged space applications can be tackled by exploiting the flexibility, high performance and long product life of FPGAs. Conventional FPGAs are subject to Single Event Upsets (SEU) due to space radiation, causing their failure. Therefore, space-graded FPGAs, such as those developed by Xilinx, are targeted within the I3DS project. Currently, the main use of the FPGA within the development of this robust end-to-end multi-sensor suite is for navigation and data preprocessing. The aim of this paper is to assess the capabilities of FPGAs to carry out complex operations, such as running navigation algorithms for space applications. The motivation for the development of the on-board software architecture is as follows: raw data, acquired from the various sensors – including, among others, a High Resolution camera, a stereo camera and a LiDAR – is pre-processed to ensure the provision of robust and optimised inputs to 3D navigation algorithms. Noise reduction and conversion into suitable formats for the successful application of navigation algorithms are therefore the main aims of the data pre-processing. Some techniques adopted in this phase include outlier rejection and data dimensionality reduction for large point clouds, e.g. from LiDAR, and geometric and radiometric correction of the images from the cameras. The pre-processed data will then feed state-of-the-art relative navigation algorithms. Some of the proposed navigation algorithms include Generalised Iterative Closest Point (GICP) for dense 3D point clouds, relative positioning with fiducial markers, and visual odometry. The system environment for the preliminary operation is a test-bench setup formed by a standard desktop computer and a non-space-graded FGA (Xilinx UltraZed-EG FPGA). The choice of FPGA was based on the similarity of this board to other spacegraded ones also provided by Xilinx. Experimental tests on the algorithms are being performed in the framework of the validation campaign for the I3DS project. Preliminary results indicate that the data pre-processing can be efficiently carried out on the FPGA board