Combinatorial conditions for the rigidity of tensegrity frameworks András Recski Budapest University of Technology and Economics La Vacquerie-et-Saint-

Slides:



Advertisements
Similar presentations
CSE 211 Discrete Mathematics
Advertisements

6.896: Topics in Algorithmic Game Theory Lecture 21 Yang Cai.
Min-Max Relations, Hall’s Theorem, and Matching-Algorithms Graphs & Algorithms Lecture 5 TexPoint fonts used in EMF. Read the TexPoint manual before you.
Covers, Dominations, Independent Sets and Matchings AmirHossein Bayegan Amirkabir University of Technology.
Chapter 8 Topics in Graph Theory
Edge-connectivity and super edge-connectivity of P 2 -path graphs Camino Balbuena, Daniela Ferrero Discrete Mathematics 269 (2003) 13 – 20.
CSE115/ENGR160 Discrete Mathematics 04/26/12 Ming-Hsuan Yang UC Merced 1.
A survey of some results on the Firefighter Problem Kah Loon Ng DIMACS Wow! I need reinforcements!
The Structure of Polyhedra Gabriel Indik March 2006 CAS 746 – Advanced Topics in Combinatorial Optimization.
Rigidity Theory and Some Applications Brigitte Servatius WPI This presentation will probably involve audience discussion, which will create action items.
Applied Combinatorics, 4th Ed. Alan Tucker
Convex Grid Drawings of 3-Connected Plane Graphs Erik van de Pol.
Applied Combinatorics, 4th Ed. Alan Tucker
On Balanced Signed Graphs and Consistent Marked Graphs Fred S. Roberts DIMACS, Rutgers University Piscataway, NJ, USA.
Tucker, Applied Combinatorics, Section 1.4, prepared by Patti Bodkin
The Equivalence between Static (rigid) and Kinematic (flexible, mobile) Systems through the Graph Theoretic Duality Dr. Offer Shai Tel-Aviv University.
1 Global Rigidity R. Connelly Cornell University.
1 Persistence Acquisition and Maintenance for Autonomous Formations Brad C. YU National ICT Australia Limited The Australian National University With Baris.
1/13/03Tucker, Applied Combinatorics, Sec Tucker, Applied Combinatorics, Sec. 1.1, Jo E-M A Graph is a set of vertices (dots) with edges (lines)
3/24/03Tucker, Section 4.31 Tucker, Applied Combinatorics, Sec. 4.3, prepared by Jo E-M Bipartite GraphMatching Some Definitions X-Matching Maximal Matching.
MCA 520: Graph Theory Instructor Neelima Gupta
D1: Matchings.
Discrete Mathematics Lecture 9 Alexander Bukharovich New York University.
Pebble games for rigidity Overview. The game of pebbling was first suggested by Lagarias and Saks, as a tool for solving a particular problem in number.
Applied Discrete Mathematics Week 10: Equivalence Relations
GRAPH Learning Outcomes Students should be able to:
Pebble Game Algorithm Demonstration
Subdivision of Edge In a graph G, subdivision of an edge uv is the operation of replacing uv with a path u,w,v through a new vertex w.
More Graphs, Subgraphs and Trees Planarity and Coloring.
Matrix Completion Problems for Various Classes of P-Matrices Leslie Hogben Department of Mathematics, Iowa State University, Ames, IA 50011
© by Kenneth H. Rosen, Discrete Mathematics & its Applications, Sixth Edition, Mc Graw-Hill, 2007 Chapter 9 (Part 2): Graphs  Graph Terminology (9.2)
Edge-disjoint induced subgraphs with given minimum degree Raphael Yuster 2012.
4.2 k-connected graphs This copyrighted material is taken from Introduction to Graph Theory, 2 nd Ed., by Doug West; and is not for further distribution.
 2. Region(face) colourings  Definitions 46: A edge of the graph is called a bridge, if the edge is not in any circuit. A connected planar graph is called.
1 Rainbow Decompositions Raphael Yuster University of Haifa Proc. Amer. Math. Soc. (2008), to appear.
Planar Graphs Graph Coloring
Conjectures Resolved and Unresolved from Rigidity Theory Jack Graver, Syracuse University SIAM conference on DISCRETE MATHEMATICS June 18-21, Dalhousie.
1 12/2/2015 MATH 224 – Discrete Mathematics Formally a graph is just a collection of unordered or ordered pairs, where for example, if {a,b} G if a, b.
Matrix Completion Problems for Various Classes of P-Matrices Leslie Hogben Department of Mathematics, Iowa State University, Ames, IA 50011
Connectivity and Paths 報告人:林清池. Connectivity A separating set of a graph G is a set such that G-S has more than one component. The connectivity of G,
Role of Rigid Components in Protein Structure Pramod Abraham Kurian.
Graph Theory and Applications
Decomposition Theory in Matching Covered Graphs Qinglin Yu Nankai U., China & U. C. Cariboo, Canada.
Graphs Lecture 2. Graphs (1) An undirected graph is a triple (V, E, Y), where V and E are finite sets and Y:E g{X V :| X |=2}. A directed graph or digraph.
Chapter 11 - Graph CSNB 143 Discrete Mathematical Structures.
Information and Control Architectures for Formation Maintenance Swarming in Natural and Engineered Systems Workshop Brian DO Anderson (work involves others)
12. Lecture WS 2012/13Bioinformatics III1 V12 Menger’s theorem Borrowing terminology from operations research consider certain primal-dual pairs of optimization.
1 GRAPH Learning Outcomes Students should be able to: Explain basic terminology of a graph Identify Euler and Hamiltonian cycle Represent graphs using.
Trees.
Theory of Computational Complexity Probability and Computing Chapter Hikaru Inada Iwama and Ito lab M1.
Applied Combinatorics, 4th Ed. Alan Tucker
Chapter 5. Optimal Matchings
Tucker, Applied Combinatorics, Sec 2.4
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 7th ed., by Kenneth H.
properties(gk)=T(laws(sj))
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 7th ed., by Kenneth H.
Applied Combinatorics, 4th Ed. Alan Tucker
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 7th ed., by Kenneth H.
5.4 T-joins and Postman Problems
Chapter 15 Graph Theory © 2008 Pearson Addison-Wesley.
Planarity.
Miniconference on the Mathematics of Computation
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 8th ed., by Kenneth H.
Existence of 3-factors in Star-free Graphs with High Connectivity
N(S) ={vV|uS,{u,v}E(G)}
Complexity Theory in Practice
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 7th ed., by Kenneth H.
Planarity.
Chapter 10.7 Planar Graphs These class notes are based on material from our textbook, Discrete Mathematics and Its Applications, 7th ed., by Kenneth H.
properties(gk)=T(laws(sj))
Presentation transcript:

Combinatorial conditions for the rigidity of tensegrity frameworks András Recski Budapest University of Technology and Economics La Vacquerie-et-Saint- Martin-de-Castries, Languedoc-Roussillon, 2007

Bar and joint frameworks Deciding the rigidity of a framework (that is, of an actual realization of a graph) is a problem in linear algebra. Deciding whether a graph is generic rigid, is a problem in combinatorics (discrete mathematics).

What can a combinatorialist do? (S)he either studies „very symmetric” structures, like square or cubic grids, or prefers „very asymmetric” ones, that is, the generic structures.

Three parts of my talk: One − story buildings as special tensegrity frameworks Tensegrity frameworks on the line Some results on the plane (to be continued by T. Jordán and Z. Szabadka today afternoon)

Tensegrity frameworks Rigid rods are resistant to compressions and tensions: ║x i − x k ║= c ik Cables are resistant to tensions only: ║x i − x k ║≤ c ik Struts are resistant to compressions only: ║x i − x k ║≥ c ik

Frameworks composed from rods (bars), cables and struts are called tensegrity frameworks. A more restrictive concept is the r- tensegrity framework, where rods are not allowed, only cables and struts. (The letter „r” means rod − free or restricted.)

Rigidity of square grids Bolker and Crapo, 1977: A set of diagonal bars makes a k X ℓ square grid rigid if and only if the corresponding edges form a connected subgraph in the bipartite graph model. Baglivo and Graver, 1983: In case of diagonal cables, strong connectedness is needed in the (directed) bipartite graph model.

Minimum # diagonals needed: B = k + ℓ − 1 diagonal bars C = 2∙max(k, ℓ ) diagonal cables (If k ≠ ℓ then C − B > 1)

Rigidity of one-story buildings Bolker and Crapo, 1977: If each external vertical wall contains a diagonal bar then instead of studying the roof of the building one may consider a k X ℓ square grid with its four corners pinned down.

Rigidity of one-story buildings Bolker and Crapo, 1977: A set of diagonal bars makes a k X ℓ square grid (with corners pinned down) rigid if and only if the corresponding edges in the bipartite graph model form either a connected subgraph or a 2-component asymmetric forest. For example, if k = 8, ℓ = 18, k ' = 4, ℓ ' = 9, then the 2-component forest is symmetric (L = K, where ℓ ' / ℓ = L, k' / k = K).

Minimum # diagonals needed: B = k + ℓ − 2 diagonal bars C = k + ℓ − 1 diagonal cables (except if k = ℓ = 1 or k = ℓ =2) (Chakravarty, Holman, McGuinness and R., 1986)

Rigidity of one-story buildings Which (k + ℓ − 1)-element sets of cables make the k X ℓ square grid (with corners pinned down) rigid? Let X, Y be the two colour classes of the directed bipartite graph. An XY-path is a directed path starting in X and ending in Y. If X 0 is a subset of X then let N(X 0 ) denote the set of those points in Y which can be reached from X 0 along XY-paths.

R. and Schwärzler, 1992: A (k + ℓ − 1)-element set of cables makes the k X ℓ square grid (with corners pinned down) rigid if and only if |N(X 0 )| ∙ k > |X 0 | ∙ ℓ holds for every proper subset X 0 of X and |N(Y 0 )| ∙ ℓ > |Y 0 | ∙ k holds for every proper subset Y 0 of Y.

Which one-story building is rigid?

Solution: Top: k = 7, ℓ = 17, k 0 = 5, ℓ 0 = 12, L < K ( < ) Bottom: k = 7, ℓ = 17, k 0 = 5, ℓ 0 = 13, L > K ( > ) where ℓ 0 / ℓ = L, k 0 / k = K.

Hall, 1935 (König, 1931): bipartite A bipartite graph with colour classes X, Y has a perfect matching if and only if |N(X 0 )| ≥ |X 0 | and holds for every proper subset X 0 of X and |N(Y 0 )| ≥ |Y 0 | holds for every proper subset Y 0 of Y.

Hetyei, 1964: A bipartite graph with colour classes X, Y has perfect matchings and every edge is contained in at least one if and only if |N(X 0 )| > |X 0 | and holds for every proper subset X 0 of X and |N(Y 0 )| > |Y 0 | holds for every proper subset Y 0 of Y.

From now on, generic structures (well, most of the time…) A one-dimensional bar-and-joint framework is rigid if and only if its graph is connected. In particular, a graph corresponds to a one- dimensional minimally rigid bar-and-joint framework if and only if it is a tree.

R. – Shai, 2005: Let the cable-edges be red, the strut-edges be blue (and replace rods by a pair of parallel red and blue edges). The graph with the given tripartition is realizable as a rigid tensegrity framework in the 1-dimensional space if and only if it is 2-edge-connected and every 2-vertex-connected component contains edges of both colours.

The necessity of the conditions is trivial. For the sufficiency recall the so called ear-decomposition of 2-vertex-connected graphs:

Realization of a single circuit

Adding ears (and stars)

Towards the 2-dimensional case Shortly recall the characterizations of the graphs of rigid bar-and-joint frameworks. Special case: minimal generic rigid graphs (when the deletion of any edge destroys rigidity). Consider at first the simple trusses:

Simple trusses (in the plane)

All the simple trusses satisfy e = 2n – 3 (n ≥ 3) and they are minimally rigid, but not every minimally rigid framework is a simple truss (consider the Kuratowski graph K 3,3, for example).

A famous minimally rigid structure: Szabadság Bridge, Budapest

Does e = 2n-3 imply that the framework is minimally rigid?

Certainly not: If a part of the framework is „overbraced”, there will be a nonrigid part somewhere else…

Maxwell (1864): If a graph G is minimal generic rigid in the plane then, in addition to e = 2n – 3, the relation e' ≤ 2n' – 3 must hold for every (induced) sub- graph G' of G.

Laman (1970): A graph G is minimal generic rigid in the plane if and only if e = 2n – 3 and the relation e' ≤ 2n' – 3 holds for every (induced) subgraph G' of G.

This is a „good characterization” of minimal generic rigid graphs in the plane, but we do not wish to check some 2 n subgraphs…

Lovász and Yemini (1982): A graph G is minimal generic rigid in the plane if and only if e = 2n – 3 and doubling any edge the resulting graph, with 2∙(n − 1) edges, is the union of two edge-disjoint trees.

A slight modification (R.,1984): A graph G is minimal generic rigid in the plane if and only if e = 2n – 3 and, joining any two vertices with a new edge, the resulting graph, with 2∙(n − 1) edges, is the union of two edge-disjoint trees.

Maxwell (1864): If a graph G is minimal generic rigid in the space then, in addition to e = 3n – 6, the relation e' ≤ 3n' – 6 must hold for every (induced) sub- graph G' of G.

However, the 3-D analogue of Laman’s theorem is not true: The double banana graph (Asimow – Roth, 1978)

We wish to generalize the above results for tensegrity frameworks: When is a graph minimal ge- neric rigid in the plane as a tensegrity framework (or as an r-tensegrity framework)?

Which is the more difficult problem?

If rods are permitted then why should one use anything else?

Which is the more difficult problem? If rods are permitted then why should one use anything else? „Weak” problem: When is a graph minimal generic rigid in the plane as an r-tensegrity framework? „Strong” problem: When is a graph with a given tripartition minimal generic rigid in the plane as a tensegrity framework?

An example to the 2-dimensional case:

The graph K 4 can be realized as a rigid tensegrity framework with struts {1,2}, {2,3} and {3,1} and with cables for the rest (or vice versa) if ‘4’ is in the convex hull of {1,2,3} …

…or with cables for two independent edges and struts for the rest (or vice versa) if none of the joints is in the convex hull of the other three.

As a more difficult example, consider the emblem of the Sixth Czech-Slovak Inter- national Symposium on Com- binatorics, Graph Theory, Algorithms and Applications (Prague, 2006, celebrating the 60 th birthday of Jarik Nešetřil).

If every bar must be replaced by a cable or by a strut then only one so- lution (and its reversal) is possible.

Critical rods cannot be replaced by cables or struts if we wish to preserve rigidity

Jordán – R. – Szabadka, 2007 A graph can be realized as a rigid d-dimensional r-tensegrity framework if and only if it can be realized as a rigid d- dimensional rod framework and none of its edges are critical.

Corollary (Laman – type): A graph G is minimal generic rigid in the plane as an r- tensegrity framework if and only if e = 2n – 2 and the relation e' ≤ 2n' – 3 holds for every proper subgraph G' of G.

Corollary (Lovász-Yemini – type): A graph is minimal generic rigid in the plane as an r-tensegrity framework if and only if it is the union of two edge-disjoint trees and remains so if any one of its edges is moved to any other position.

The „strong problem” is open for the 2-dimensional case. Here is a more complicated example.

Rigidity and connectivity A graph is generic rigid in the 1- dimensional space as an r-tensegrity framework if and only if it is 2-edge- connected. For the generic rigidity in the plane as an r-tensegrity framework, a graph must be 2- vertex-connected and 3-edge-connected. However, neither 3-vertex-connectivity nor 4-edge-connectivity is necessary.

A rigid r-tensegrity framework. Its graph is neither 3-vertex- connected, nor 4-edge-connected.

To be continued in the afternoon…

Thanks for your attention Reprints available from