Intensive introduction of robotic systems is a modern priority for further automation of human activities. Recent theoretical and practical developments in robotics have made it possible to introduce robots in areas of practical activities previously dominated by humans. Modern trend in robotics is in creating state of the art robotic systems with increased autonomy and expanded functionality. This will allow to relieve human, leaving him supervision functions. An emerging task in robotics is also to create an environment, assisting to create and introduce new perspective robotic systems, also bearing modernization capability. This can be done through improving of modern approaches of creating robotic systems. We foresee necessity to change some of robots’ life-cycle stages, which would allow to rapidly introduce new effective robots into production. The article in its beginning studies some most emerging directions in robotics and new ideas for more effective robotic systems design. During this one should find a balance between introducing drastically new technologies in new robot and perfectioning already existing technologies. Authors propose to use so-called modular-platform based approach for creating new robots. Within it they imply typical structure of a robot, suggesting to use basic platform as a basement for building new robots with varying usefull load. In such case same platform can be used for building inspection robots, unmanned transport systems, unmanned retransmitter etc. The paper presents some already built examples of the approach. Final part of the paper discusses advantages given by application of this approach.

The article presents an algorithm for controlling a ground unmanned vehicle. The main task is to obtain a solution to control problems that allows you to transfer an unmanned vehicle from the initial position to a given final position at a certain time. Currently, autonomous vehicles are being actively introduced in all areas. Including in Russia, you can find unmanned trucks on the federal highway. Given the development of microprocessor technology and the significant economic benefits of using unmanned vehicles, this task is relevant. A lot of research in the field of control of unmanned vehicles concerns the issue of their use in urban environments and on rough terrain. In this paper, we present a solution to the problem of optimal control of an unmanned vehicle using the maximum principle. The problem of optimal control is solved in a deterministic setting with an integro-terminal criterion. The solution of the two-point boundary value problem arising from the maximum principle was carried out using Newton’s method. The ranges of initial values of conjugate variables are obtained, which ensure the convergence of calculations. For the chosen mathematical model of the course movement of the car, solutions to the problem were obtained. The results of numerical simulation are presented, showing the possibility of using the proposed algorithm to control an unmanned vehicle under various initial and final conditions. The developed algorithm has been successfully applied in the presence of a penalty zone. The algorithm can be used when applying the concept of " flexible trajectories" in the tasks of controlling moving objects.

Currently, the development of a self-driving car (SDC) is becoming increasingly popular, the full autonomy of which is achieved by automatic control of all its driving modes and maneuvers, including parking — the most common maneuver. The problem of parking automation is of particular relevance, as far as it allows not only to facilitate the process of safe parking, but also to increase the density of parked cars. The paper considers the control problem of automatic parking of SDC. The statement and formalization of the control problem of car parking taking into account the mechanical and spatial constraints ensuring the safety of the parking maneuver are given. Both classical and modern control methods of automatic car parking are considered. The classical control method of SDC parking is based on the utilization of widely used Dubins and Reeds-Shepp traffic models ensuring fast acting optimal car parking. At the same time, the algorithm of a fast-growing random tree RRT was used to construct a path between two points. Due to randomization, an important advantage of this algorithm is its independence from the geometric representation and dimension of the modeled environment of the car. The modern control methods of SDC parking are based on the use of intelligent methods and technologies. In present paper in contrast to the classical, "untrained" methods, the control method of parking based on machine learning is used. The problem of synthesis of control algorithm of SDC parking based on the machine learning method with reinforcement is posed and solved. A car parking algorithm implemented in Python using mathematical libraries Matplotlib and NumPy is synthesized. Computer verification of the synthesized algorithm was carried out and optimal values of machine learning parameters were determined.

The paper proposes a method for controlling tension forces in statically indeterminable cable-driven systems based on the non-negative least squares method with control of singular or near-singular solutions and a complete search of all possible cable configurations. For cable-driven parallel robots the problem of controlling the cable tension forces is critical, because in the absence of control the cable tension forces are distributed unevenly, which leads to reduced robustness of the system, increased energy consumption and increased deterioration. And in special cases of cable system configuration the tension forces become so great that they lead to cable breaks. At the same time, correction of cable tension force distribution should not lead to significant deviations from the specified position of the mobile platform or, formulating the problem in terms of forces, to violation of kinetostatic equations. Thus, the problem of controlling the tension forces in the cable parallel robot system is solved as a problem of optimizing the tension forces of the cables according to the criteria of minimizing the norm of their vector in the configuration space and minimizing the norm of incoherence of the vector of forces and moments in the operational space of the robot. The developed algorithm is based on the solution of underdetermined systems of linear algebraic equations with finding the minimum least squares norms and subsequent zeroing of negative components of the solution vector. The paper considers examples of the solution of the set problem for the lower cable group of a construction 3D printer based on a cable-driven robot and for a 12-cable system

This work explores displaced orbits of solar sails below the Moon’s south pole, near the L2 libration point in the Earth-Moon system. Light pressure provides acceleration for displaced orbits. These orbits enable continuous communication and observation of the Moon’s south polar region, where a lunar base is planned. Linearized dynamic equations yield analytical solutions of displaced orbits, which are either quasi-periodic or periodic. Quasi-periodic orbits have varying altitudes of hundreds of kilometers and a period of about a year, while periodic orbits have fixed altitudes аnd the same period. A sliding mode controller maintains the orbits using sail attitude angles and reflectivity as control variables. With a reflective area to mass ratio of 18 m2/kg, the displaced heights of quasiperiodic and periodic orbits near L2 are 2010.38 km and 2210.06 km, respectively. Numerical simulations confirm the controller’s effectiveness for both orbit types

The problem of constructing models with the desired properties, which are used in the algorithmic support of the sighting and navigation complex of the aircraft, has been studied. The quality of the used mathematical models largely determines the accuracy of the correction of the sighting and navigation system, therefore it is proposed to build models directly during the flight using some evolutionary algorithm. For example, using a self-organization algorithm. The ensemble of selection criteria for the self-organization algorithm includes various criteria that determine the properties of the selected models. Depending on the field of application of the models, they are given the desired properties by means of a self-organization algorithm with a variable ensemble of selection criteria. The selection ensemble consists of general, special criteria, as well as a controlled combination of qualitative criteria that selectively improve the performance of models. When the flight mode changes, the influence of one or another special criterion on the process under study changes. The change in the ensemble of selection criteria for the self-organization algorithm occurs automatically during the flight. Degrees of observability, controllability and parametric identifiability are used as improved qualitative characteristics. Over time, the degree of observability, controllabi lity, and parametric identifiability may change. Components that were well observable over time can become poorly observable. The weakly observable components of the state vector, although they are formally observable, in practice are not processed by estimation algorithms, since their evaluation is possible only on sufficiently large intervals of the system operation. A similar situation develops with models in the study of the quality of their controllability, as well as with the parameters of models during their identification. An algorithm for controlling the quality selection criteria and a diagram of the algorithm for generating models during the correction of a promising sighting and navigation complex of an aircraft are presented. Mathematical modeling has been carried out for various flight modes of the aircraft, such as straight flight, flight at different altitudes. The results of the simulation showed the efficiency and effectiveness of the proposed algorithmic solutions