Mission Design and GNC for In-Orbit Demonstration of Active Debris Removal Technologies with CubeSats

Federico Belloni, Volker Gass, Christophe Dominique Paccolat, Camille Sébastien Pirat, Muriel Richard, Reto Wiesendanger
2015
Conference paper

Abstract

Within the frame of the ESA’s General Support Technology Programme, EPFL studied two In-Orbit Demonstration (IOD) missions using CubeSat technologies. These IODs aim at alleviating the technical risk inherent to new technologies required for Active Debris Removal (ADR) of large space objects, by using small and low-cost CubeSat systems. Rendezvous and docking with uncooperative debris was only partially demonstrated and still raises technological issues. To test technologies such as the navigation and Rendezvous (RV) sensors or capture systems, our studies show that CubeSat missions are appropriate. Already, Guidance, Navigation & Control (GNC), communications and power technologies have successfully been miniaturized and the corresponding equipments are now available to the CubeSat community. This fact extends the range of feasible CubeSat missions from the initial flight of simple sensors to more complex systems. This paper presents two CubeSat ADR experiments and demonstrates how mission design and GNC can serve the verification of navigation sensors performances as well as the validation of uncooperative debris capture using a net. Each mission is composed of a Chaser and a Target. The former being an 8 Units (8U) CubeSat and the latter a 4U, launched together in a 12U deployer. Both satellites are 3-axis attitude controlled. The Chaser has in addition 3 Degrees of Freedom (DoF) translation capability using 1mN cold gas thrusters. Both CubeSats will carry GNSS receivers to assist in the determination of range and relative velocity. The global positioning and attitude data of the Target will be transmitted to the Chaser using an inter-satellite link having the additional capacity to measure the corresponding range. This system provides a reference validation for the RV sensors. The relative position and velocity to be controlled are fully observable. Thus a linear quadratic regulator is appropriate to ensure robust and optimal control. Based on the mission design, various close inspection configurations are demonstrated. To emphasize the feasibility of such missions, a system approach will be briefly addressed leading to a complete description of both CubeSats including mass, power, volume and data budgets. Both missions are analyzed using a 6 DoF simulator. The performances and absolute errors of the GNC as well as fuel consumption are provided. Power consumption, telecom capability and thermal aspects will be shown for sake of completeness. Current issues and limitations of the current GNC will be discussed, as well as conclusions regarding the feasibility of such missions.

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Federico Belloni, Volker Gass, Christophe Dominique Paccolat, Camille Sébastien Pirat, Muriel Richard, Reto Wiesendanger
2015
Conference paper

Abstract

Official source

https://infoscience.epfl.ch/record/215429?ln=en

About this result

Related concepts (24)

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Mission Design and GNC for In-Orbit Demonstration of Active Debris Removal Technologies with CubeSats

Federico Belloni, Volker Gass, Christophe Dominique Paccolat, Camille Sébastien Pirat, Muriel Richard, Reto Wiesendanger

Within the frame of the ESA's General Support Technology Programme, two In-Orbit Demonstration (IOD) missions using CubeSat technologies were studied. These IODs aim at alleviating the technical risk inherent to new technologies required for Active Debris Removal (ADR) of large space objects, by using small and low-cost CubeSat systems. Rendezvous and docking with uncooperative debris has been only partially demonstrated and still raises technological issues. To test technologies such as the navigation and Rendezvous (RV) sensors or capture systems, our studies show that CubeSat missions are appropriate. Already, Guidance, Navigation and Control (GNC), communications and power technologies have successfully been miniaturised and the corresponding equipments are now available to the CubeSat community. This fact extends the range of feasible CubeSat missions from the initial flight of simple sensors to more complex systems. This paper presents two CubeSat ADR experiments and demonstrates how mission design and GNC can serve the verification or navigation sensors performances as well as the validation of uncooperative debris capture using a net. Each mission is composed of a Chaser and a Target. The former being an 8 Units (8U) CubeSat and the latter a 4U, launched together in a 12U deployer. Both satellites are 3-axis attitude controlled. The Chaser has in addition 3 Degrees of Freedom (DoF) translation capability using 1 mN cold gas thrusters. Both CubeSats will carry GNSS receivers to assist in the determination of range and relative-velocity. The global positioning and attitude data or the Target will be transmitted to the Chaser using an inter-satellite link having the additional capacity to measure the corresponding range. This system provides a reference validation for the RV sensors. The relative position and velocity to be controlled are fully observable. Thus a linear quadratic regulator is appropriate to ensure robust and optimal control. Based on the mission design, various close inspection configurations are demonstrated. To emphasise the feasibility of such missions, a system approach will be briefly addressed. Both missions are analysed using a 6 DoF simulator. The performances and absolute errors of the GNC as well as fuel consumption are provided. Power consumption, Telecom capability and thermal aspects will be shown for sake of completeness. Current issues and limitations of the CubeSat GNC will be discussed, as well as conclusions regarding the feasibility of such missions.

Elsevier2016

Mechatronic elements and haptic rendering for computer-assisted minimally invasive surgery training

Thomas Moix

Technological advances of the last decades enabled the development of a set of new medical techniques that differ from traditional open surgery. These techniques, referred to as minimally invasive surgery (MIS), involve complex instruments and imaging devices to reach and treat anatomical regions through small incisions or natural entry points resulting in reduced trauma and shorter recovery time. For the surgeons, MIS introduces unnatural hand-eye coordination and anatomical representation that require specific training. One alternative is the use of virtual reality (VR) simulations of MIS procedures coupled to input devices mimicking instruments used by surgeons. To achieve high-fidelity with such a computer-assisted training system, the input device also provides the sensations experienced during a procedure with force reflective technology, often referred to as haptics. This work explores the mechatronic aspects implied in the realization of such a haptic device for MIS training applications. An analysis of different MIS procedures enables to draw two categories: lumen-guided and cavity procedures. A simple classification of the required mechanism can be extracted from these observations. To fulfil the requirements, an implementation should follow a series of guidelines in terms of actuation and power transmission that are presented. The interactions between a human operator and a haptic interface involve both force and motion. Impedance control generates a force command based on the position of the haptic interface. This process, called haptic rendering, is an integrate part of the VR environment. This work proposes to extend impedance control with model-based compensation of the dynamics and non-linearities (such as friction) of the haptic device. Due to sensitivity to model uncertainties, the proposed control architecture is completed by a parallel implicit force controller. Since the computational load of VR simulation for complex anatomies is high, update rates reach 20 to 30 Hz. These frequencies are not sufficient to control a haptic device and meet the sensitivity requirements of the human sensory system. Therefore, in such system a multirate approach is introduced. A model is proposed for the dynamics of a haptic interface and its user. Based on this model, the effect of the introduced implicit force controller is studied and different interfacing techniques between the VR simulation and the haptic controller are evaluated. Since force sensing is a requirement for the implementation of the proposed implicit forcecontroller, a technique using infrared reflective sensors is proposed. A modelling method for such sensors is introduced and implementation issues for force sensing are discussed. Finally, the topics discussed in this work are applied to the development of a computer-assisted training system for Interventional Radiology.

EPFL2005

Vision-based inertial-aided navigation is gaining ground due to its many potential applications. In previous decades, the integration of vision and inertial sensors was monopolised by the defence industry due to its complexity and unrealistic economic burden. After the technology advancement, high-quality hardware and computing power became reachable for the investigation and realisation of various applications. In this thesis, a mapping system by vision-aided inertial navigation was developed for areas where GNSS signals are unreachable, for example, indoors, tunnels, city canyons, forests, etc. In this framework, a methodology on the integration of vision and inertial sensors was presented, analysed and tested when the only available information at the beginning is a number of features with known location/coordinates (with no GNSS signals accessibility), thus employing the method of "SLAM: Simultaneous Localisation And Mapping". SLAM is a term used in the robotics community to describe the problem of mapping the environment and at the same time using this map to determine (or to help in determining) the location of the mapping device. In addition to this, a link between the robotics and geomatics community was established where briefly the similarities and differences were outlined in terms of handling the navigation and mapping problem. Albeit many differences, the goal is common: developing a "navigation and mapping system" that is not bounded to the limits imposed by the used sensors. Classically, terrestrial robotics SLAM is approached using LASER scanners to locate the robot relative to a structured environment and to map this environment at the same time. However, outdoors robotics SLAM is not feasible with LASER scanners alone due to the environment's roughness and absence of simple geometric features. Recently in the robotics community, the use of visual methods, integrated with inertial sensors, has gained an interest. These visual methods rely on one or more cameras (or video) and make use of a single Kalman Filter with a state vector containing the map and the robot coordinates. This concept introduces high non-linearity and complications to the filter, which then needs to run at high rates (more than 20 Hz) with simplified navigation and mapping models. In this study, SLAM is developed using the Geomatics Engineering approach. Two filters are used in parallel: the Least-Squares Adjustment (LSA) for feature coordinates determination and the Kalman Filter (KF) for navigation correction. For this, a mobile mapping system (independent of GPS) is introduced by employing two CCD cameras (one metre apart) and one IMU. Conceptually, the outputs of the LSA photogrammetric resection (position and orientation) are used as the external measurements for the inertial KF. The filtered position and orientation are subsequently employed in the Photogrammetric intersection to map the surrounding features that are used as control points for the resection in the next epoch. In this manner, the KF takes the form of a navigation only filter, with a state vector containing the corrections to the navigation parameters. This way, the mapping and localisation can be updated at low rates (1 to 2 Hz) and use more complete modelling. Results show that this method is feasible with limitation induced from the quality of the images and the number of used features. Although simulation showed that (depending on the image geometry) determining the features' coordinates with an accuracy of 5-10 cm for objects at distances of up to 10 metres is possible, in practice this is not achieved with the employed hardware and pixel measurement techniques. Navigational accuracies depend as well on the quality of the images and the number and accuracy of the points used in the resection. While more than 25 points are needed to achieve centimetre accuracy from resection, they have to be within a distance of 10 metres from the cameras; otherwise, the resulting resection output will be of insufficient accuracy and further integration quality deteriorates. The initial conditions highly affect SLAM performance; these are the method of IMU initialisation and the a-priori assumptions on error distribution. The geometry of the system will furthermore have a consequence on possible applications. To conclude, the development consisted in establishing a mathematical framework, as well as implementing methods and algorithms for a novel integration methodology between vision and inertial sensors. The implementation and validation of the software have presented the main challenges, and it can be considered the first of a kind where all components were developed from scratch, with no pre-existing modules. Finally, simulations and practical tests were carried out, from which initial conclusions and recommendations were drawn to build upon. It is the author's hope that this work will stimulate others to investigate further this interesting problem taking into account the conclusions and recommendations sketched herein.

EPFL2006

Mission Design and GNC for In-Orbit Demonstration of Active Debris Removal Technologies with CubeSats

Federico Belloni, Volker Gass, Christophe Dominique Paccolat, Camille Sébastien Pirat, Muriel Richard, Reto Wiesendanger

Elsevier2016

Mechatronic elements and haptic rendering for computer-assisted minimally invasive surgery training

Thomas Moix

EPFL2005

EPFL2006