Implementation of receptor geometric models in the problems of automated layout design in aviation technology

Aviation technologies


Nyi N. H.1*, Markin L. V.1**, Sosedko A. A.2***

1. Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia
2. Kompany “ACA” , 10/1, M. Jalil St.,115573, Russia



The subject of the article is the development of geometrical models and algorithms of computer-aided design of the connecting tracks which are comparable to the extent of already placed objects (so-called physical trace) with their sizes. The additional requirements of routing design of trace are restrictions of smoothness to the flow lines of the track.
As the solution of this requirement, we will use the discrete method (receptor model) based on a grid which can simulate the basic designs of the tracks in layout space. Such models are used for trace of multilayered printed-circuit boards; but the direct use of these well-known algorithms to solve the problem formulated above is impossible because the smoothness (the given set of radius of curvature) of the track and safe distance between the obstacles objects and the track are not secured.
We have modified the most perfect algorithms for discrete path finding, the Dijkstra’s and A* (AStar) algorithms. The base principle of these algorithms is close to the methodology of the receptor geometrical models, and their great advantage is the simplicity of obstacle determination via receptor code (0 or 1). We have to eliminate the defect of known algorithms such as the ignoring of the obstacles before collision on them.
The main modifications of the known algorithms are the heuristic optimization of the algorithm which determines the choice of the search direction to target, so that allows one the avoiding of the bypass of many extra vertices. Another modification is the choice of the search direction as defined by heuristic methods. Usually path finding algorithms use 4- or 8-directions method which can determine how the next child node will be selected from parent node (for 2D and 3D models respectively). In our 3D multi-directional algorithm we use 26 adjacent vertices to find a way to destinations. So this method can be 300-1200 times faster the path finding process compared with known algorithms.
Using a receptor method as geometrical modeling for finding track has both the advantages and the disadvantages. The advantage of receptor model is the unique simplicity of determination of mutual non-intersection condition of already placed objects. The disadvantage is the impossibility of creation of objects with high order of smoothness. Therefore we need to make modifications to exiting algorithms for most effective routing track as offered method. Example of its implementation is designing of canal among already placed objects. In this article, we use our method for possible layout design of air intake hose among existing configuration of a motor compartment of ASA-2 light plane.
The assessment of accuracy of the offered algorithm showed that it depends on discretization of a receptor matrix and at its size of 0,2 mm makes 0,12 mm that is quite enough for a design stage of the new track. Rapid growth of productivity of computers makes discrete receptor models more and more attractive and more and more demanded in practice of design of hi-tech equipment.


engineering design, pathfinding, receptor models, physical trace, canal surface , avoid obstacles, smoothing trajectory, service area accuracy


  1. Gavrilov V.N. Avtomatizirovannaya komponovka pribornykh otsekov letatel’nykh apparatov (The automated configuration of instrument in the compartments of aircraft), Moscow, Mashinostroenie,1988, 136 p.
  2. Stoyan Yu.G., Yakovlev S.V. Matematicheskie modeli i optimizatsionnye metody geometricheskogo proektirovaniya (Mathematical models and optimizing methods of geometrical design), Kiev, Nauk. dumka, 1986, 268 p.
  3. Stoyan Yu.G., Gil’ N.I. Metody i algoritmy razmeshcheniya ploskikh geometricheskikh ob«ektov (Methods and algorithms of placement of flat geometrical objects), Kiev, Nauk. dumka, 1976, 248 p.
  4. Osipov V.A. Mashinnye metody proektirovaniya nepreryvno-karkasnykh poverkhnostei (Machine methods of design of continuous and frame surfaces), Moscow, Mashinostroenie, 1979 248 p.
  5. Dijkstra E. W. A note on two problems in connation with graphs, Numerische Mathematik, 1959, vol. 1, pp. 269-271.
  6. Hart, P. E.; Nilsson, N. J.; Raphael, B.: A Formal Basis for the Heuristic Determination of Minimum Cost Paths, IEEE Transactions on Systems Science and Cybernetics,1968, SSC4, 4 (2), pp. 100-107.
  7. Rabin S. AI Game Programming Wisdom, Charles River Media, 2002, 672 p.
  8. Khammapun Khantanapoka, Krisana Chinnasarn «Path finding of 2D & 3D Game Real-Time Strategy with Depth Direction A*Algorithm for Multi-Layer», Proceedings of Eighth International Symposium on Natural Language Processing, Thailand, 2009, pp. 184-188.
  9. Wichmann D. R. Automated Route Finding on Digital Terrains , Project Report, Graphics Group, Dept. of Computer Science, University of Auckland, New Zealand, 2004, pp.107-112.
  10. Sity Lin. Razrabotka metodov i geometricheskikh modelei analiza nezapolnennykh prostranstv v zadachakh razmeshcheniya (Development of methods and geometrical models of the analysis of blank spaces in the tasks of accommodation) иза незаполненных пространств в задачах размещения ), Abstract of dissertation , Мoscow, МАИ, 2011, 24 p.

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