40 research outputs found

    ΠœΠ΅Ρ‚ΠΎΠ΄ ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ мобильного Ρ€ΠΎΠ±ΠΎΡ‚Π° Π² ΠΏΠΎΠ»Π΅ источников-Ρ€Π΅ΠΏΠ΅Π»Π»Π΅Ρ€ΠΎΠ²

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    РассматриваСтся ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Π° ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚ΠΈΡ€ΠΎΠ²ΠΊΠΈ Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ двиТСния робототСхничСской ΠΏΠ»Π°Ρ‚Ρ„ΠΎΡ€ΠΌΡ‹ (РВП) Π½Π° плоскости с Ρ†Π΅Π»ΡŒΡŽ сниТСния вСроятности Π΅Ρ‘ пораТСния/обнаруТСния Π² ΠΏΠΎΠ»Π΅ ΠΊΠΎΠ½Π΅Ρ‡Π½ΠΎΠ³ΠΎ числа источников-Ρ€Π΅ΠΏΠ΅Π»Π»Π΅Ρ€ΠΎΠ². ΠšΠ°ΠΆΠ΄Ρ‹ΠΉ ΠΈΠ· Ρ‚Π°ΠΊΠΈΡ… источников описан матСматичСской модСлью Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠ³ΠΎ Ρ„Π°ΠΊΡ‚ΠΎΡ€Π° противодСйствия цСлостности ΠΈΠ»ΠΈ скрытности РВП. Указанная ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Π° основана, с ΠΎΠ΄Π½ΠΎΠΉ стороны, Π½Π° понятии Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π½ΠΎΠΉ вСроятностной Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΈ систСмы источников-Ρ€Π΅ΠΏΠ΅Π»Π»Π΅Ρ€ΠΎΠ², ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‰Π΅ΠΌ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Ρ‚ΡŒ ΡΡ‚Π΅ΠΏΠ΅Π½ΡŒ влияния этих источников Π½Π° Π΄Π²ΠΈΠΆΡƒΡ‰ΡƒΡŽΡΡ РВП. Из этого понятия Π²Ρ‹Ρ‚Π΅ΠΊΠ°Π΅Ρ‚ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΠ΅ΠΌΠ°Ρ здСсь Π² качСствС показатСля ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ Ρ†Π΅Π»Π΅Π²ΠΎΠΉ Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ Π²Π΅Ρ€ΠΎΡΡ‚Π½ΠΎΡΡ‚ΡŒ Π΅Ρ‘ ΡƒΡΠΏΠ΅ΡˆΠ½ΠΎΠ³ΠΎ прохоТдСния. Π‘ Π΄Ρ€ΡƒΠ³ΠΎΠΉ стороны, эта ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Π° базируСтся Π½Π° Ρ€Π΅ΡˆΠ΅Π½ΠΈΠΈ Π»ΠΎΠΊΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Π·Π°Π΄Π°Ρ‡, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡŽΡ‰ΠΈΡ… ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹Π΅ участки исходной Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ с ΡƒΡ‡Π΅Ρ‚ΠΎΠΌ нахоТдСния Π² ΠΈΡ… окрСстностях ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½Ρ‹Ρ… источниковрСпСллСров с Π·Π°Π΄Π°Π½Π½Ρ‹ΠΌΠΈ ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€Π°ΠΌΠΈ. ΠšΠ°ΠΆΠ΄Ρ‹ΠΉ ΠΈΠ· Ρ‚Π°ΠΊΠΈΡ… источников характСризуСтся ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π»ΠΎΠΌ, частотой воздСйствия, радиусом дСйствия ΠΈ ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€Π°ΠΌΠΈ спада поля. ΠšΠΎΡ€Ρ€Π΅ΠΊΡ‚ΠΈΡ€ΠΎΠ²ΠΊΠ° Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ происходит ΠΈΡ‚Π΅Ρ€Π°Ρ†ΠΈΠΎΠ½Π½ΠΎ ΠΈ ΡƒΡ‡ΠΈΡ‚Ρ‹Π²Π°Π΅Ρ‚ Ρ†Π΅Π»Π΅Π²ΠΎΠ΅ Π·Π½Π°Ρ‡Π΅Π½ΠΈΠ΅ вСроятности прохоТдСния. ΠžΡΠ½ΠΎΠ²Π½Ρ‹ΠΌ ΠΎΠ³Ρ€Π°Π½ΠΈΡ‡Π΅Π½ΠΈΠ΅ΠΌ Π½Π° Π²Π°Ρ€ΠΈΠ°Ρ†ΠΈΡŽ исходной Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ являСтся максимально допустимоС ΠΎΡ‚ΠΊΠ»ΠΎΠ½Π΅Π½ΠΈΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½Π½ΠΎΠΉ Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ ΠΎΡ‚ исходной. Если Ρ‚Π°ΠΊΠΎΠ³ΠΎ ограничСния Π½Π΅Ρ‚, Ρ‚ΠΎ Π·Π°Π΄Π°Ρ‡Π° ΠΌΠΎΠΆΠ΅Ρ‚ ΠΏΠΎΡ‚Π΅Ρ€ΡΡ‚ΡŒ смысл, ΠΏΠΎΡΠΊΠΎΠ»ΡŒΠΊΡƒ Ρ‚ΠΎΠ³Π΄Π° ΠΌΠΎΠΆΠ½ΠΎ Π²Ρ‹Π΄Π΅Π»ΠΈΡ‚ΡŒ ΠΎΠ±Π»Π°ΡΡ‚ΡŒ, ΠΎΡ…Π²Π°Ρ‚Ρ‹Π²Π°ΡŽΡ‰ΡƒΡŽ всС прСпятствия ΠΈ источники, ΠΈ ΠΎΠ±ΠΎΠΉΡ‚ΠΈ Π΅Ρ‘ ΠΏΠΎ ΠΏΠ΅Ρ€ΠΈΠΌΠ΅Ρ‚Ρ€Ρƒ. ΠŸΠΎΡΡ‚ΠΎΠΌΡƒ осущСствляСтся поиск Ρ‚Π°ΠΊΠΎΠ³ΠΎ локального экстрСмума, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ соотвСтствуСт допустимой ΠΊΡ€ΠΈΠ²ΠΎΠΉ Π² смыслС ΡƒΠΊΠ°Π·Π°Π½Π½ΠΎΠ³ΠΎ ограничСния. ΠŸΡ€Π΅Π΄Π»Π°Π³Π°Π΅ΠΌΠ°Ρ Π² настоящСй Ρ€Π°Π±ΠΎΡ‚Π΅ итСрационная ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Π° позволяСт ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΡ‚ΡŒ поиск ΡΠΎΠΎΡ‚Π²Π΅Ρ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΡ… Π»ΠΎΠΊΠ°Π»ΡŒΠ½Ρ‹Ρ… максимумов вСроятности прохоТдСния РВП Π² ΠΏΠΎΠ»Π΅ Π½Π΅ΡΠΊΠΎΠ»ΡŒΠΊΠΈΡ… ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ»ΡŒΠ½ΠΎ располоТСнных ΠΈ ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… источников Π² Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΉ окрСстности исходной Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ. Π’Π½Π°Ρ‡Π°Π»Π΅ ставится ΠΈ Ρ€Π΅ΡˆΠ°Π΅Ρ‚ΡΡ Π·Π°Π΄Π°Ρ‡Π° ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ ΠΏΡ€ΠΈ условии двиТСния Π² ΠΏΠΎΠ»Π΅ ΠΎΠ΄Π½ΠΎΠ³ΠΎ источника с ΠΎΠ±Π»Π°ΡΡ‚ΡŒΡŽ дСйствия Π² Π²ΠΈΠ΄Π΅ ΠΊΡ€ΡƒΠ³ΠΎΠ²ΠΎΠ³ΠΎ сСктора, Π·Π°Ρ‚Π΅ΠΌ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹ΠΉ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ распространяСтся Π½Π° случай Π½Π΅ΡΠΊΠΎΠ»ΡŒΠΊΠΈΡ… Π°Π½Π°Π»ΠΎΠ³ΠΈΡ‡Π½Ρ‹Ρ… источников. Основной ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΠΎΠΉ исслСдования являСтся Π²Ρ‹Π±ΠΎΡ€ ΠΎΠ±Ρ‰Π΅Π³ΠΎ Π²ΠΈΠ΄Π° Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΎΠ½Π°Π»Π° Π² ΠΊΠ°ΠΆΠ΄ΠΎΠΉ Ρ‚ΠΎΡ‡ΠΊΠ΅ исходной ΠΊΡ€ΠΈΠ²ΠΎΠΉ, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π΅Π³ΠΎ коэффициСнтов настройки. Показано, Ρ‡Ρ‚ΠΎ Π²Ρ‹Π±ΠΎΡ€ этих коэффициСнтов настройки Π΅ΡΡ‚ΡŒ адаптивная ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Π°, Π²Ρ…ΠΎΠ΄Π½Ρ‹ΠΌΠΈ ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹ΠΌΠΈ ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΉ ΡΠ²Π»ΡΡŽΡ‚ΡΡ Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π½Ρ‹Π΅ гСомСтричСскиС Π²Π΅Π»ΠΈΡ‡ΠΈΠ½Ρ‹, ΠΎΠΏΠΈΡΡ‹Π²Π°ΡŽΡ‰ΠΈΠ΅ Ρ‚Π΅ΠΊΡƒΡ‰ΡƒΡŽ Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΡŽ Π² ΠΏΠΎΠ»Π΅ источников. Для устранСния осцилляций, Π²ΠΎΠ·Π½ΠΈΠΊΠ°ΡŽΡ‰ΠΈΡ… вслСдствиС Π»ΠΎΠΊΠ°Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΏΡ€Π΅Π΄Π»Π°Π³Π°Π΅ΠΌΠΎΠΉ ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Ρ‹, ΠΏΡ€ΠΈΠΌΠ΅Π½ΡΡŽΡ‚ΡΡ стандартныС ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Ρ‹ ΠΌΠ΅Π΄ΠΈΠ°Π½Π½ΠΎΠ³ΠΎ сглаТивания. Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ модСлирования ΠΏΠΎΠΊΠ°Π·Ρ‹Π²Π°ΡŽΡ‚ Π²Ρ‹ΡΠΎΠΊΡƒΡŽ ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΏΡ€ΠΎΡ†Π΅Π΄ΡƒΡ€Ρ‹ для ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚ΠΈΡ€ΠΎΠ²ΠΊΠΈ Ρ€Π°Π½Π΅Π΅ спланированной Ρ‚Ρ€Π°Π΅ΠΊΡ‚ΠΎΡ€ΠΈΠΈ

    Optimization of mobile robot movement on a plane with finite number of repeller sources

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    The paper considers the problem of planning a mobile robot movement in a conflict environment, which is characterized by the presence of areas that impede the robot to complete the tasks. The main results of path planning in the conflict environment are considered. Special attention is paid to the approaches based on the risk functions and probabilistic methods. The conflict areas, which are formed by point sources that create in the general case asymmetric fields of a continuous type, are observed. A probabilistic description of such fields is proposed, examples of which are the probability of detection or defeat of a mobile robot. As a field description, the concept of characteristic probability function of the source is introduced; which allows us to optimize the movement of the robot in the conflict environment. The connection between the characteristic probability function of the source and the risk function, which can be used to formulate and solve simplified optimization problems, is demonstrated. The algorithm for mobile robot path planning that ensures the given probability of passing the conflict environment is being developed. An upper bound for the probability of the given environment passing under fixed boundary conditions is obtained. A procedure for optimizing the robot path in the conflict environment is proposed, which is characterized by higher computational efficiency achieved by avoiding the search for an exact optimal solution to a suboptimal one. A procedure is proposed for optimizing the robot path in the conflict environment, which is characterized by higher computational efficiency achieved by avoiding the search for an exact optimal solution to a suboptimal one. The proposed algorithms are implemented in the form of a software simulator for a group of ground-based robots and are studied by numerical simulation methods

    Trajectory Planning Algorithms in Two-Dimensional Environment with Obstacles

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    This article proposes algorithms for planning and controlling the movement of a mobile robot in a two-dimensional stationary environment with obstacles. The task is to reduce the length of the planned path, take into account the dynamic constraints of the robot and obtain a smooth trajectory. To take into account the dynamic constraints of the mobile robot, virtual obstacles are added to the map to cover the unfeasible sectors of the movement. This way of accounting for dynamic constraints allows the use of map-oriented methods without increasing their complexity. An improved version of the rapidly exploring random tree algorithm (multi-parent nodes RRT – MPN-RRT) is proposed as a global planning algorithm. Several parent nodes decrease the length of the planned path in comprise with the original one-node version of RRT. The shortest path on the constructed graph is found using the ant colony optimization algorithm. It is shown that the use of two-parent nodes can reduce the average path length for an urban environment with a low building density. To solve the problem of slow convergence of algorithms based on random search and path smoothing, the RRT algorithm is supplemented with a local optimization algorithm. The RRT algorithm searches for a global path, which is smoothed and optimized by an iterative local algorithm. The lower-level control algorithms developed in this article automatically decrease the robot’s velocity when approaching obstacles or turning. The overall efficiency of the developed algorithms is demonstrated by numerical simulation methods using a large number of experiments

    Determining crystal phase purity in c-BP through X-ray absorption spectroscopy

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    Citation: Determining crystal phase purity in c-BP through X-ray absorption spectroscopy. S. P. Huber, V. V. Medvedev, E. Gullikson, B. Padavala, J. H. Edgar, R. W. E. van de Kruijs, F. Bijkerk, and D. Prendergast. Phys. Chem. Chem. Phys. 19 8174--8187 (2017) 10.1039/c6cp06967cWe employ X-ray absorption near-edge spectroscopy at the boron K-edge and the phosphorus L2,3-edge to study the structural properties of cubic boron phosphide (c-BP) samples. The X-ray absorption spectra are modeled from first-principles within the density functional theory framework using the excited electron core-hole (XCH) approach. A simple structural model of a perfect c-BP crystal accurately reproduces the P L2,3-edge, however it fails to describe the broad and gradual onset of the B K-edge. Simulations of the spectroscopic signatures in boron 1s excitations of intrinsic point defects and the hexagonal BP crystal phase show that these additions to the structural model cannot reproduce the broad pre-edge of the experimental spectrum. Calculated formation enthalpies show that, during the growth of c-BP, it is possible that amorphous boron phases can be grown in conjunction with the desired boron phosphide crystalline phase. In combination with experimental and theoretically obtained X-ray absorption spectra of an amorphous boron structure, which have a similar broad absorption onset in the B K-edge spectrum as the cubic boron phosphide samples, we provide evidence for the presence of amorphous boron clusters in the synthesized c-BP samples

    Diffraction of EUV radiation on free-standing grid structures: theory and experiment

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    Application of metal mesh filters were recently proposed for suppression of scattered infrared radiation in laser-produced plasma EUV sources. However, performance of such filters in EUV region has not been thoroughly analyzed yet. We have investigated EUV transmittance of different gird filters. The rigorous coupled-wave analysis has been used in numerical study of diffraction efficiencies. Comparison of numerical results with scalar theory of diffraction has been performed. Dependence of EUV transmittance on grid geometrical parameters has been found. Finally, in-band EUV transmittance has been measured at normal incidence. Experimental and theoretical results are found to be in a good agreement
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