1. Technology of detection and prevention of polyconflicts collisions in complex dynamic systems
The intensive development of UAV/UAS/RPAS technologies (Unmanned Aircraft Vehicles, Unmanned Aircraft Systems, Remotely Piloted Aircraft Systems) over the past decades has led to the fact that drones have become actively used in many sectors of the economy: agriculture, construction, transport, telecommunications, etc. According to ResearchAndMarkets.com forecasts [1], the volume of the UAV market by 2025 will amount to $ 40-45 billion, with an average annual growth rate of about 15%. The total volume of investments in projects related to UAS/RPAS technologies by mid-2020 amounted to more than $ 4 billion [2].

         The most promising areas for using drones in urban environments are passenger transportation (drones-taxi), as well as the delivery of goods, food, medicines, etc.

         Consequently, in a few years, intensive traffic of a large number of manned, remotely piloted and unmanned dynamic objects (DO) is expected in the urban airspace. This, in its turn, requires the availability of an appropriate air traffic management and control systems.

         To solve this problem, the «Technology of detection and avoidance of polyconflicts of collision in complex dynamic systems» is proposed.

Technology provide:

         — guaranteed safe achievement of the target positions of DO in conditions of polyconflicts of collisions between them, taking into account their priority and functional state;
         — control of the conflict-free motion of an unlimited set of DO in a given space, including in terminal zones and zones of merging of their traffic flows, in the presence of static and dynamic obstacles and forbidden zones of any geometry and configuration;
         — autonomy of DO and their safe motion in accordance with the concept of «Free Flight», under conditions of degradation of the functional state of DO, in case of their failures, as well as in conditions of perturbation and counteraction of an aggressive environment;
         — unification of DO into dynamic robotic formations with a given structure and geometry;
         — guaranteed solution of the navigation problem with a given accuracy for each DO in case of unstable operation of satellite navigation systems (GPS, GLONASS, GALILEO, BEIDOU) in an urban environment;
         — distributed control of DO based on the use of SNS technology (Subscriber — Network — Subscriber), invariant to the time delays of data packet transmission.

Application areas of the technology: air traffic control systems for manned, remotely piloted and unmanned aerial vehicles in restricted airspace; control of the movement of taxi drones and other unmanned aerial vehicles in urban airspace; transport, logistics, construction, security, monitoring, as well as the entertainment and delivery industries.

2. Spatial motion control technology for dynamic robotic formations (DRF)

         Unmanned Aerial Vehicles (UAV) become more popular for use in different domains due significant list of advantages in comparison to manned aircraft such as low manufacturing and operational costs, flexibilityin accommodating different payloads, risk reduction ofhuman lives (no pilot or crew), and so on.

Especially, these benefits can feel in case of multi-UAVs flight performance, so-called UAVs swarming, when a group of UAVs forms a structure with indicated shape and start to perform flight mission with respect to separation minima. The issues that appear in this case connected with multiple conflict detection and resolution between UAVs and any static or dynamic obstacles.

         Group use of drones is a promising new direction in the development of robotic technologies around the world.

         A new technology, including algorithmic and software control of conflict-free trajectory motion of formations (swarm, herd, flock, group etc.) of robotic dynamic objects, is proposed.
          The technology provides: autonomous target movement of DRF; bypassing static and dynamic obstacles, restricted areas; flexible adaptive structural self-organization of DRF; to control parametric and structural reconfiguration in conditions of destructive action of the external environment and degradation of the functional state of the elements of DRF.

         Application areas of the technology: high-precision farming, mapping, monitoring of objects and the earth’s surface, construction, security of objects, transport, delivery of goods, air show.

3. Indoor positioning and navigation technology

         All over the world, the indoor positioning system (IPS) market is in the active phase of the “first wave”. The indoor services market is rated today as the most promising and capital-intensive. In fact, this is the only area in IT that is currently not occupied and does not have a clearly defined technology leader.

          The market for indoor navigation technologies in 2017 crossed the $ 6.92 billion mark. According to Opus Research, indoor navigation became a new step in sales promotions market in stores and reached $ 10 billion in 2018.

ABI Research estimated indoor navigation in the geo advertising market at $ 13 billion per year in 2018. Expert agency MarketsandMarkets predicts that the segment will grow to $ 23.6 billion by 2023.

Google experts believe the fast-growing indoor navigation market will soon overtake the GPS market. GPS / GLONASS navigation technology works only in the open air, where there are no obstacles for the satellite signal. However, according to Source Strategy Analytics, 80% of mobile internet connections are made indoors rather than outdoors. According to a Deloitte report, by 2022, at least a quarter of all precision digital navigation uses will take place indoors.

Forbes predicts that the turnover of companies that have switched to Industry 4.0 technologies, which include indoor navigation, will reach the $ 1.5 trillion mark by 2022, and their efficiency will exceed the current level of productivity by more than 7 times.

The proposed technology allows to: determine 3D coordinates of objects with an accuracy of 5 cm; monitor the movement of people, equipment, goods in restricted spaces; identify events of dangerous approach; predict dangerous and abnormal situations associated with getting into hazardous areas.

Application areas of the technology: in Industry 4.0 technologies; smart home, including with technologies to support people with disabilities; Internet of Things (IoT) market; medical service; environmental monitoring; work of rescue services; in banks, museums, airports, train stations, shopping centers, offices, parking lots, warehouses; retail, logistics and marketing; robotic production; construction.

It can be used to solve the problems of high-precision local outdoor navigation without the use of satellite navigation systems.

4. Air navigation technology for dynamic objects

The technology is based on algorithms of non-invariant compensation integration of aircraft navigation equipment of manned and unmanned dynamic objects, such as aviation (aircraft, helicopters, unmanned aerial vehicles), space (launch vehicles, satellites), ground (cars, trains), sea (boats, marine unmanned aerial vehicles) ) mobile means.

The technology makes it possible to ensure the autonomy and noise immunity of the solution to the navigation problem (without the use of satellite navigation systems) on board dynamic objects. The technology meets the increased requirements for the accuracy, dependability and reliability of navigation support.

Any onboard navigation facilities for positional, velocity and goniometric measurements in any configuration can be used as navigation correctors. In each case, various combinations of navigation measuring sensors and systems are used.

The technology has been tested for the navigation system of a small unmanned aerial vehicle. At the same time, the processing of navigation measurements from inertial meters (accelerometers and gyroscopes — angular rate sensor), as well as correctors such as airspeed sensors, angles of attack and slip, vertical angles (pyrometric sensors) and a three-component magnetometer is implemented.