Current projects

Area: Strategic Thinking

Project “Advanced roadmapping”
A methodology for model-based evaluation of technology infusion for improved strategic technology development. Industrial implementation of the methodology with a toolkit to support planning and decision making. Project with Airbus Group.

Corporate technology roadmapping serves the strategic management to decide on technology development trying to maximize the potential return through successful future products and services.

We develop for our industrial partner new methods and tools to support the roadmapping process applying a model-based approach. Our method includes the analysis of historical data on the product tradespace and apply novel mathematical models for 2-dimensional pareto-front forecasting. Taking into account data about competitors we perform game-theoretic strategy simulation to inform decision making. We also use delphi surveys for structured expert opinion elicitation and consensus finding.

Project manager Dominik Knoll

Concurrent Engineering Design Laboratory
Maintenance of the the facility (software upgrades, new methods development). Main tool for concurrent design sessions for other projects in the strategic thinking department.

Project managers: Anton Ivanov and Alexander Platonov

Strategic analysis of space applications
Modelling of upcoming industrial and government initiatives. New telecommunication and navigation services, remote sensing in digital economy. Science mission planning.

Project manager: Anton Ivanov

Model based systems engineering for aerospace systems

Systems engineering is a discipline intended to support complex system developments by braking down a product into a number of relatively independent subsystems. Traditionally, management of system’s structure was performed with documents. That approach has a number of drawbacks. The main goal of model-based systems engineering is the infusion of models into systems engineering processes, such as architecting, interface specification, managing emerging systems behavior, etc. during complex products development. We leverage subsystem-level performance attributes into economical indicators of a complex system, which is essential to make informed decisions about product flexibility in changing environment, its performance and feasibility, technology infusion, interaction with other systems in early project stages. We specialize on modelling complex aerospace systems, such as satellites and aircrafts. Starting from the beginning of XX century human-made systems have significantly grown in complexity. Eventually that resulted in the creation of huge systems like modern commercial aircrafts, rockets and satellites which can contain up to several million individual parts intended to fly together. Systems engineering is a discipline aimed to overcome the complexity of the systems we build in order to fulfill the requirements of different stakeholders. The team focuses on architecting the framework to predict the performance of various aerial and satellite systems performing their target missions and interaction with their operational environment. Satellites, aircrafts, base stations and their instruments could be modelled and visualized in different scenarios of operation. The framework is intended for decision making support for chief engineers and architects of various aerospace systems. Main scientific interest of the group is to model and predict the impact of various low-level system change on higher-level performance. For instance, certain architectural or technological decision can be traced up to product performance and subsequently to economical viability of corresponding service. Subsequently, given a set of key decisions, the design could be optimized for the operation in a given environment.

Project engineers: Petr Mukhachev; Alexander Kharlan;

Area: Autonomous systems

Swarm of satellites
Development of autonomous satellite swarms and constellations. Design and manufacturing of satellite platforms, interaction with payload manufacturers.

Robust software for robotic platforms
There is a trend in current satellite systems design process that the size of software increases in geometric progression, which leads, eventually, to the creation of the non-ergonomic and overcomplicated interfaces. Even though hardware is sufficiently standardized in the form of commercial-of-the-shelf components, software is always specific to the type of payload. It leads to the differentiation of spacecraft designs, depending on the agencies, which were responsible for the manufacturing of those systems. Each of these projects should undergo the validation process, which becomes costly in the late development stages. It is clearly seen on the V-diagram of the system engineering. A reasonable solution is to explicitly specify and validate the system requirements at the early design stages, ensuring correctness by construction. So, the rigorous approach was introduced to build complex systems – architecture-based design, which composes simpler systems and revise them on meeting given properties, specifications and constraints. The incremental construction occurs via Behavior-Interaction-Priorities (BIP) framework.

The BIP is a formal framework, which coordinates the behavior of a set of atomic model components. Each individual component has imposed behavioural contract and well-defined properties. An architecture in BIP is a model, where the strict hierarchy of components and their interactions are stated. If an architecture, applied to the set of components in one layer, meets requirements and constraints, the layer’s design is validated. The design model is incrementally built, integrating previous layer’s architectures, preventing the generation of non-established interactions and behaviours. Construction of the model-based system allows to apply automatic transformations to obtain executable code from formally defined high-level models. The example of the High-level interaction model you can see on the picture (Mavridou A. et al. Formal Aspects of Component Software. FACS 2016. Lecture Notes in Computer Science, vol 10231. Springer, Cham)

Project manager: Anton Afanasiev

Advanced testing techniques for space platforms
During this project we implement adjustment of contact elements thermal interfaces for the best thermal design of small satellites. This process is being simultaneously with structure design. MATLAB Simulink is used to create simple thermal model of the satellite.

Project manager: Nikolay Mullin

Control algorithms for swarm platforms
This project is about mixture of structural design, thermal design and modern manufacturing technology such as 3D-printing. Small-size CubeSat 3U is developed as a technology demonstration.

The old way of designing and launching a single satellite to perform a certain task can be changed by designing groups of thousands miniature satellites that possess a much broader potential. Such setup increases the reliability of the system as the instruments of individual satellites coordinate to function together as in a large distributed system. Various configurations can be considered such as trains of satellites (which follow one after another along the same orbit), formations that maintain rigorous geometry (e.g. to reflect sunlight to the Earth’s surface, and thus producing pixel images in the sky), swarms that act as a group, while fulfilling a common task, or evenly spread giant networks surveilling the Earth’s entire surface. The shapes of such networks can be tuned to fulfill different tasks. Various groups of satellites in different constellations may be virtually connected together if need be, to enhance their coverage and power consumption. These groups might even include special service satellites, whose function is to repair the broken ones, de-orbit the defunct ones or transfer the operational ones to specific orbits. Deployment of the miniature satellites’ swarms is considered to be cheap and fast. Vast populations of such satellites can be let out of a single large central satellite in orbit. Swarms can comprise simplistic units that detect certain events and exchange signals with each other and larger more complicated spacecraft that act as analysis hubs. Finally, swarms or constellations can be employed as distributed artificial intelligence. They can exhibit collective behaviour, such as self-organization, transformability, self-learning and simultaneous sensing over large areas.

Project managers: Dmitriy Pritykin; Shamil Biktimirov

Skoltech Rocket
Design and manufacturing of small-sized rocket for IREC championship

Project owners: Nickolay Mullin, Ivan Sobolev

Robot solutions for warehousing
Project manager: Dzmitry Tsetseroukou

Haptics and swarms of drones
Project manager: Dzmitry Tsetseroukou

Drones for apple trees disease detection
Project manager: Dzmitry Tsetseroukou

Area: Space enabled services

Forest classification using hyper-spectral data
Using hyper-spectral data, create high precision classification algorithms for forests. Knowledge translation between drone based imaging and satellite based imaging.

Project manager: Alexander Platonov

Project engineers: Vasili Mosin, Roberto Aguilar

Solar weather prediction
The project will contribute to the improvement of the scientific understanding, forecasting and mitigation of extreme space weather events. This aspect is getting more and more important, as our modern society is increasingly relying on satellite systems for communication, navigation, Earth/weather/climate observations, catastrophe management, economy transactions, etc., and thus is highly vulnerable on space weather effects. This is also reflected in the foundation of ESA’s Space Situational Awareness Programme, where Space Weather is a Key Area. The project also is important for the ground breaking missions such as Parker Probe Plus (NASA, launch 2018) and Solar Orbiter (ESA, launch 2020).The project is aimed to conduct the research in solar-terrestrial physics from close to the Sun to Earth’s magnetosphere focusing on the following topics:

  • Detection of eruptive events on Sun (coronal mass ejections and accompanying solar events);
  • Forecasting of solar wind speed at Earth;
  • Forecasting of geomagnetic storms and polar aurora;
  • Solar activity forecasting;
  • Scientific and service products.

In each of the subfields, the approach is research-to-operations (R2O), which brings together the forefront of research with applications, thus yielding significant benefits through the delivery of new public and commercial space-based services and development of new technologies.

Project manager: Tatiana Podladchikova

Wearable platform for vital signs monitoring
The project is dedicated to the development of clinical decision support system on arrhythmia detection powered by prolonged monitoring wearables and improvement of quality of diagnostics of cardiac arrhythmias. Detection of cardiac arrhythmia events at the very early stage could help to deliver a forehanded care and to prevent further complications.

Project manager: Tatiana Podladchikova

Localisation system for unmanned vehicle
The project aims at the increasing of effectiveness automobile transport localisation on the basis of disclosure of the system tracking uncertainty. It will allow us to perform an accurate and uninterrupted tracking and control of leading to the reliable decisions and risk minimisation on the basis of obtained estimates. It is planned to develop innovative methods for the noise statistics identification and parameter estimations for nonlinear systems that is of prime importance for the robust tracking in conditions of uncertainty on simulations and real-time experimental data, as well as methods of adaptive cruise control and prevention of collisions combining data from sensors (GPS, radar, odometry, camera, etc).

Project manager: Tatiana Podladchikova

Distributed Ground stations
Create software to enable distributed and highly flexible UHF / VHF stations to receive and transmit data from small satellites. Multi-agent scheduling methods.

Project manager: Anton Ivanov