4 research outputs found
ΠΠ½Π°Π»ΠΈΠ· Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ°Π·ΡΠ΅ΡΠΈΠΌΠΎΡΡΠΈ ΠΏΡΠΈ ΡΠ±ΠΎΡΠΊΠ΅ ΡΠ»ΠΎΠΆΠ½ΡΡ ΠΈΠ·Π΄Π΅Π»ΠΈΠΉ ΠΊΠ°ΠΊ Π·Π°Π΄Π°ΡΠ° ΠΏΡΠΈΠ½ΡΡΠΈΡ ΡΠ΅ΡΠ΅Π½ΠΈΠΉ
Computer aided assembly planning (CAAP) of complex products is an important and urgent problem of state-of-the-art information technologies. A configuration of the technical system imposes fundamental restrictions on the design solutions of the assembly process. The CAAP studies offer various methods for modelling geometric constraints. The most accurate results are obtained from the studies of geometric obstacles, which prohibit the part movement to the appropriate position in the product, by the collision analysis methods. An assembly of complex technical systems by this approach requires very high computational costs, since the analysis should be performed for each part and in several directions.The article describes a method for minimizing the number of direct checks for geometric obstacle avoidance. Introduces a concept of the geometric situation to formalize such fragments of a structure, which require checking for geometric obstacle avoidance. Formulates two statements about geometric heredity during the assembly. Poses the task of minimizing the number of direct checks as a non-antagonistic two-person game on two-colour painting of an ordered set. Presents the main decision criteria under uncertainty. To determine the best criterion, a computational experiment was carried out on painting the ordered sets with radically different structural properties. All the connected ordered sets are divided into 13 subclasses, each of which includes structurally similar instances. To implement the experiment, a special program has been developed that creates a random ordered set in the selected subclass, implements a game session on its coloration, and also collects and processes statistical data on a group of the homogeneous experiments.The computational experiment has shown that in all subclasses of the partial orders, the Hurwitz criterion with a confidence coefficient of 2/3 and that of Bayes-Laplace demonstrate the best results. The Wald and Savage criteria have demonstrated the worst results. In the experiment, a difference between the best and worst results reached 70%. With increasing height (maximum number of levels) of an ordered set, this difference tends to grow rapidly. In the subclass of pseudo-chains, all criteria showed approximately equal results.The game model of geometric obstacles avoidance allows formalizing data on geometric heredity and obtaining data on the composition and the minimum number of configurations, the test of which objectifies all existing-in-the-product geometric constraints on the movements of parts during assembly.ΠΠ²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΡΠ±ΠΎΡΠΊΠΈ ΡΠ»ΠΎΠΆΠ½ΡΡ
ΠΈΠ·Π΄Π΅Π»ΠΈΠΉ β ΡΡΠΎ Π²Π°ΠΆΠ½Π°Ρ ΠΈ Π°ΠΊΡΡΠ°Π»ΡΠ½Π°Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ° ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ. Π€ΡΠ½Π΄Π°ΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΠ΅ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΈΡ Π½Π° ΠΏΡΠΎΠ΅ΠΊΡΠ½ΡΠ΅ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΡΠ±ΠΎΡΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΠ΅ΡΠ΅Π΄Π΅Π»Π° Π½Π°ΠΊΠ»Π°Π΄ΡΠ²Π°Π΅Ρ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
ΠΏΠΎ CAAP ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ²ΡΠ·Π΅ΠΉ. Π‘Π°ΠΌΡΠ΅ ΡΠΎΡΠ½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ Π΄Π°Π΅Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠ΅ΠΏΡΡΡΡΠ²ΠΈΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ Π·Π°ΠΏΡΠ΅ΡΠ°ΡΡ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΠ΅ Π΄Π΅ΡΠ°Π»ΠΈ Π² ΡΠ»ΡΠΆΠ΅Π±Π½ΠΎΠ΅ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ Π² ΠΈΠ·Π΄Π΅Π»ΠΈΠΈ, ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ Π°Π½Π°Π»ΠΈΠ·Π° ΡΡΠΎΠ»ΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΠΉ. ΠΠ»Ρ ΡΠ±ΠΎΡΠΊΠΈ ΡΠ»ΠΎΠΆΠ½ΡΡ
ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΈΡΡΠ΅ΠΌ Π΄Π°Π½Π½ΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΡΡΠ΅Π±ΡΠ΅Ρ ΠΎΡΠ΅Π½Ρ Π²ΡΡΠΎΠΊΠΈΡ
Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
Π·Π°ΡΡΠ°Ρ, ΠΏΠΎΡΠΊΠΎΠ»ΡΠΊΡ Π°Π½Π°Π»ΠΈΠ· ΡΠ»Π΅Π΄ΡΠ΅Ρ Π²ΡΠΏΠΎΠ»Π½ΠΈΡΡ Π΄Π»Ρ ΠΊΠ°ΠΆΠ΄ΠΎΠΉ Π΄Π΅ΡΠ°Π»ΠΈ ΠΈ Π² Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΈΡ
Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡΡ
.Π ΡΡΠ°ΡΡΠ΅ ΠΎΠΏΠΈΡΠ°Π½ ΠΌΠ΅ΡΠΎΠ΄ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠ»Π° ΠΏΡΡΠΌΡΡ
ΠΏΡΠΎΠ²Π΅ΡΠΎΠΊ Π½Π° Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΡΡ ΡΠ°Π·ΡΠ΅ΡΠΈΠΌΠΎΡΡΡ. ΠΠ²Π΅Π΄Π΅Π½ΠΎ ΠΏΠΎΠ½ΡΡΠΈΠ΅ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ, ΠΊΠΎΡΠΎΡΠΎΠ΅ ΡΠΎΡΠΌΠ°Π»ΠΈΠ·ΡΠ΅Ρ ΡΠ°ΠΊΠΈΠ΅ ΡΡΠ°Π³ΠΌΠ΅Π½ΡΡ ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ, Π΄Π»Ρ ΠΊΠΎΡΠΎΡΡΡ
ΡΡΠ΅Π±ΡΠ΅ΡΡΡ ΠΏΡΠΎΠ²Π΅ΡΠΊΠ° Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΡΡ ΡΠ°Π·ΡΠ΅ΡΠΈΠΌΠΎΡΡΡ. Π‘ΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Ρ Π΄Π²Π° ΡΡΠ²Π΅ΡΠΆΠ΄Π΅Π½ΠΈΡ ΠΎ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π½Π°ΡΠ»Π΅Π΄ΡΡΠ²Π΅Π½Π½ΠΎΡΡΠΈ ΠΏΡΠΈ ΡΠ±ΠΎΡΠΊΠ΅. ΠΠ°Π΄Π°ΡΠ° ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠ»Π° ΠΏΡΡΠΌΡΡ
ΠΏΡΠΎΠ²Π΅ΡΠΎΠΊ ΠΏΠΎΡΡΠ°Π²Π»Π΅Π½Π° ΠΊΠ°ΠΊ Π½Π΅Π°Π½ΡΠ°Π³ΠΎΠ½ΠΈΡΡΠΈΡΠ΅Π½ΡΠΊΠ°Ρ ΠΈΠ³ΡΠ° Π΄Π²ΡΡ
Π»ΠΈΡ ΠΏΠΎ ΠΎΠΊΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π° Π² Π΄Π²Π° ΡΠ²Π΅ΡΠ°. ΠΡΠΈΠ²Π΅Π΄Π΅Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ ΠΊΡΠΈΡΠ΅ΡΠΈΠΈ ΠΏΡΠΈΠ½ΡΡΠΈΡ ΡΠ΅ΡΠ΅Π½ΠΈΠΉ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ. ΠΠ»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π»ΡΡΡΠ΅Π³ΠΎ ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½Ρ ΠΏΠΎ ΠΎΠΊΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½Π½ΡΡ
ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ² Ρ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΡΠ½ΠΎ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌΠΈ ΡΡΡΡΠΊΡΡΡΠ½ΡΠΌΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌΠΈ. ΠΡΠ΅ ΡΠ²ΡΠ·Π½ΡΠ΅ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½Π½ΡΠ΅ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π° ΡΠ°Π·Π±ΠΈΡΡ Π½Π° 13 ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠΎΠ², Π² ΠΊΠ°ΠΆΠ΄ΡΠΉ ΠΈΠ· ΠΊΠΎΡΠΎΡΡΡ
Π²Ρ
ΠΎΠ΄ΡΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎ ΠΏΠΎΠ΄ΠΎΠ±Π½ΡΠ΅ ΡΠΊΠ·Π΅ΠΌΠΏΠ»ΡΡΡ. ΠΠ»Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ° ΡΠΎΠ·Π΄Π°Π½Π° ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½Π°Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ°, ΠΊΠΎΡΠΎΡΠ°Ρ ΡΠΎΠ·Π΄Π°Π΅Ρ ΡΠ»ΡΡΠ°ΠΉΠ½ΠΎΠ΅ ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½Π½ΠΎΠ΅ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²ΠΎ Π² Π²ΡΠ±ΡΠ°Π½Π½ΠΎΠΌ ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠ΅, ΡΠ΅Π°Π»ΠΈΠ·ΡΠ΅Ρ ΠΈΠ³ΡΠΎΠ²ΠΎΠΉ ΡΠ΅Π°Π½Ρ ΠΏΠΎ Π΅Π³ΠΎ ΠΎΠΊΡΠ°ΡΠΈΠ²Π°Π½ΠΈΡ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΎΠ±ΠΈΡΠ°Π΅Ρ ΠΈ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°Π΅Ρ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΏΠΎ Π³ΡΡΠΏΠΏΠ΅ ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΡΡ
ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠΎΠ².ΠΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½Ρ ΠΏΠΎΠΊΠ°Π·Π°Π», ΡΡΠΎ Π²ΠΎ Π²ΡΠ΅Ρ
ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠ°Ρ
ΡΠ°ΡΡΠΈΡΠ½ΡΡ
ΠΏΠΎΡΡΠ΄ΠΊΠΎΠ² Π»ΡΡΡΠΈΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ Ρ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² ΠΡΡΠ²ΠΈΡΠ° Ρ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠΎΠΌ Π΄ΠΎΠ²Π΅ΡΠΈΡ 2/3 ΠΈ ΠΠ°ΠΉΠ΅ΡΠ°-ΠΠ°ΠΏΠ»Π°ΡΠ°. Π₯ΡΠ΄ΡΠΈΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΏΡΠΎΠ΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°Π»ΠΈ ΠΊΡΠΈΡΠ΅ΡΠΈΠΈ ΠΠ°Π»ΡΠ΄Π° ΠΈ Π‘Π΅Π²ΠΈΠ΄ΠΆΠ°. Π Π°Π·Π½ΠΈΡΠ° ΠΌΠ΅ΠΆΠ΄Ρ Π»ΡΡΡΠΈΠΌΠΈ ΠΈ Ρ
ΡΠ΄ΡΠΈΠΌΠΈ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌΠΈ Π΄ΠΎΡΡΠΈΠ³Π°Π»Π° Π² ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ΅ 70%. ΠΡΠ° ΡΠ°Π·Π½ΠΈΡΠ° ΠΈΠΌΠ΅Π΅Ρ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡ ΠΊ Π±ΡΡΡΡΠΎΠΌΡ ΡΠΎΡΡΡ Ρ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ΠΌ Π²ΡΡΠΎΡΡ (ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΈΡΠ»Π° ΡΡΠΎΠ²Π½Π΅ΠΉ) ΡΠΏΠΎΡΡΠ΄ΠΎΡΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π°. Π ΠΏΠΎΠ΄ΠΊΠ»Π°ΡΡΠ΅ ΠΏΡΠ΅Π²Π΄ΠΎΡΠ΅ΠΏΠ΅ΠΉ Π²ΡΠ΅ ΠΊΡΠΈΡΠ΅ΡΠΈΠΈ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ ΠΏΡΠΈΠΌΠ΅ΡΠ½ΠΎ ΡΠ°Π²Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ.ΠΠ³ΡΠΎΠ²Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ°Π·ΡΠ΅ΡΠΈΠΌΠΎΡΡΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΠΎΡΠΌΠ°Π»ΠΈΠ·ΠΎΠ²Π°ΡΡ Π΄Π°Π½Π½ΡΠ΅ ΠΎ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π½Π°ΡΠ»Π΅Π΄ΡΡΠ²Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ ΠΏΠΎΠ»ΡΡΠΈΡΡ Π΄Π°Π½Π½ΡΠ΅ ΠΎ ΡΠΎΡΡΠ°Π²Π΅ ΠΈ ΠΌΠΈΠ½ΠΈΠΌΠ°Π»ΡΠ½ΠΎΠΌ ΡΠΈΡΠ»Π΅ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΠΉ, ΠΏΡΠΎΠ²Π΅ΡΠΊΠ° ΠΊΠΎΡΠΎΡΡΡ
ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²ΠΈΡΡΠ΅Ρ Π²ΡΠ΅ Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΈΡ Π½Π° Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ Π΄Π΅ΡΠ°Π»Π΅ΠΉ ΠΏΡΠΈ ΡΠ±ΠΎΡΠΊΠ΅, ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΠ΅ Π² ΠΈΠ·Π΄Π΅Π»ΠΈΠΈ
On reconfiguration of disks in the plane and related problems
We revisit two natural reconfiguration models for systems of disjoint objects in the plane: translation and sliding. Consider a set of n pairwise interior-disjoint objects in the plane that need to be brought from a given start (initial) configuration S into a desired goal (target) configuration T, without causing collisions. In the translation model, in one move an object is translated along a fixed direction to another position in the plane. In the sliding model, one move is sliding an object to another location in the plane by means of an arbitrarily complex continuous motion (that could involve rotations). We obtain various combinatorial and computational results for these two models: (I) For systems of n congruent disks in the translation model, Abellanas et al. showed that 2n β 1 moves always suffice and β8n/5 β moves are sometimes necessary for transforming the start configuration into the target configuration. Here we further improve the lower bound to β5n/3 β β 1, and thereby give a partial answer to one of their open problems. (II) We show that the reconfiguration problem with congruent disks in the translation model is NPhard, in both the labeled and unlabeled variants. This answers another open problem of Abellanas et al. (III) We also show that the reconfiguration problem with congruent disks in the sliding model is NP-hard, in both the labeled and unlabeled variants. (IV) For the reconfiguration with translations of n arbitrary convex bodies in the plane, 2n moves are always sufficient and sometimes necessary
Translation separability of sets of polygons
We consider the problem of separating a set of polygons by a sequence of translations (one such collision-free translation motion for each polygon). If all translations are performed in a common direction the separability problem so obtained has been referred to as the uni-directional separability problem; for different translation directions, the more general multi-directional separability problem arises. The class of such separability problems has been studied previously and arises e.g. in computer graphics and robotics. Existing solutions to the uni-directional problem typically assume the objects to have a certain predetermined shape (e.g., rectangular or convex objects), or to have a direction of separation already available. Here we show how to compute all directions of unidirectional separability for sets of arbitrary simple polygons. The problem of determining whether a set of polygons is multi-directionally separable had been posed by G.T. Toussaint. Here we present an algorithm for solving this problem which, in addition to detecting whether or not the given set is multidirectionally separable, also provides an ordering in which to separate the polygons. In case that the entire set is not multi-directionally separable, the algorithm will find the largest separable subset