Part I: Linkages c: Locked Chains Joseph ORourke Smith College (Many slides made by Erik Demaine)

Slides:



Advertisements
Similar presentations
Part I: Paper d: Protein Folding
Advertisements

Part III: Polyhedra b: Unfolding
Part II: Paper a: Flat Origami
Part III: Polyhedra a: Folding Polygons
Part I: Linkages e: Unit-Length Locked Chains? Joseph ORourke Smith College.
Part II: Paper b: One-Cut Theorem Joseph ORourke Smith College (Many slides made by Erik Demaine)
Folding & Unfolding in Computational Geometry: Introduction Joseph ORourke Smith College (Many slides made by Erik Demaine)
GRAPHS OF THE POLAR EQUATIONS r = a ± b cos θ r = a ± b sin θ
1 Adornments, Flowers, and Kneser-Poulsen Bob Connelly Cornell University (visiting University of Cambridge)
Splines I – Curves and Properties
Mechanics of Machines Dr. Mohammad Kilani
M. Belkin and P. Niyogi, Neural Computation, pp. 1373–1396, 2003.
Spatial Embedding of Pseudo-Triangulations Peter Braß Institut für Informatik Freie Universität Berlin Berlin, Germany Franz Aurenhammer Hannes Krasser.
Orthogonal Drawing Kees Visser. Overview  Introduction  Orthogonal representation  Flow network  Bend optimal drawing.
Approximations of points and polygonal chains
© University of Wisconsin, CS559 Spring 2004
Active Contours, Level Sets, and Image Segmentation
Discrete Differential Geometry Planar Curves 2D/3D Shape Manipulation, 3D Printing March 13, 2013 Slides from Olga Sorkine, Eitan Grinspun.
 Distance Problems: › Post Office Problem › Nearest Neighbors and Closest Pair › Largest Empty and Smallest Enclosing Circle  Sub graphs of Delaunay.
Visibility Graph Team 10 NakWon Lee, Dongwoo Kim.
Geometric Modeling Notes on Curve and Surface Continuity Parts of Mortenson, Farin, Angel, Hill and others.
Problems related to the Kneser-Poulsen conjecture Maria Belk.
Linear Programming and The Carpenter’s Ruler Presentation by Perouz Taslakian COMP566 – Fall 2004.
Computing the Fréchet Distance Between Folded Polygons
Basic Feasible Solutions: Recap MS&E 211. WILL FOLLOW A CELEBRATED INTELLECTUAL TEACHING TRADITION.
Image Segmentation and Active Contour
Corp. Research Princeton, NJ Cut Metrics and Geometry of Grid Graphs Yuri Boykov, Siemens Research, Princeton, NJ joint work with Vladimir Kolmogorov,
Graph Drawing Introduction 2005/2006. Graph Drawing: Introduction2 Contents Applications of graph drawing Planar graphs: some theory Different types of.
Realizability of Graphs Maria Belk and Robert Connelly.
Rectangle Visibility Graphs: Characterization, Construction, Compaction Ileana Streinu (Smith) Sue Whitesides (McGill U.)
Trajectory Simplification
Is the following graph Hamiltonian- connected from vertex v? a). Yes b). No c). I have absolutely no idea v.
Lower Bounds for the Ropelength of Reduced Knot Diagrams by: Robert McGuigan.
CS 326 A: Motion Planning robotics.stanford.edu/~latombe/cs326/2003/index.htm Configuration Space – Basic Path-Planning Methods.
Chapter 4: Straight Line Drawing Ronald Kieft. Contents Introduction Algorithm 1: Shift Method Algorithm 2: Realizer Method Other parts of chapter 4 Questions?
On Reconfiguring Radial Trees Yoshiyuki Kusakari Akita Prefectural University JCDCG (Sun.)
1 Representing Curves and Surfaces. 2 Introduction We need smooth curves and surfaces in many applications: –model real world objects –computer-aided.
1 Numerical geometry of non-rigid shapes Non-Euclidean Embedding Non-Euclidean Embedding Lecture 6 © Alexander & Michael Bronstein tosca.cs.technion.ac.il/book.
Geometric Probing with Light Beacons on Multiple Mobile Robots Sarah Bergbreiter CS287 Project Presentation May 1, 2002.
Geometry is everywhere by : Laura González  Solid figures are 3D figures that have length, width and heigth.  For example :  Sphere Faces:0 Vertices:0.
Complexity results for three-dimensional orthogonal graph drawing maurizio “titto” patrignani third university of rome graph drawing 2005.
Week 13 - Wednesday CS361.
CS 376 Introduction to Computer Graphics 04 / 23 / 2007 Instructor: Michael Eckmann.
Planar Graphs: Euler's Formula and Coloring Graphs & Algorithms Lecture 7 TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.:
Planning Near-Optimal Corridors amidst Obstacles Ron Wein Jur P. van den Berg (U. Utrecht) Dan Halperin Athens May 2006.
Introduction to Computational Geometry Hackson
Week Aug-17 – Aug-22 Introduction to Spatial Computing CSE 5ISC Some slides adapted from Worboys and Duckham (2004) GIS: A Computing Perspective, Second.
October 9, 2003Lecture 11: Motion Planning Motion Planning Piotr Indyk.
CS 376 Introduction to Computer Graphics 04 / 20 / 2007 Instructor: Michael Eckmann.
Nonoverlap of the Star Unfolding Boris Aronov and Joseph O’Rourke, 1991 A Summary by Brendan Lucier, 2004.
Approximation algorithms for TSP with neighborhoods in the plane R 郭秉鈞 R 林傳健.
Complexity results for three-dimensional orthogonal graph drawing maurizio patrignani third university of rome graph drawing dagstuhl
Course 8 Contours. Def: edge list ---- ordered set of edge point or fragments. Def: contour ---- an edge list or expression that is used to represent.
I go on and on in both directions What am I?. A line.
Greg Humphreys CS445: Intro Graphics University of Virginia, Fall 2003 Parametric Curves & Surfaces Greg Humphreys University of Virginia CS 445, Spring.
CSCE 441: Keyframe Animation/Smooth Curves (Cont.) Jinxiang Chai.
Optimal Path Planning Using the Minimum-Time Criterion by James Bobrow Guha Jayachandran April 29, 2002.
Polygon Definition Bounded by a closed circuit of straight-line segment. Term Edge : straight line segment Vertices : points.
Two Finger Caging of Concave Polygon Peam Pipattanasomporn Advisor: Attawith Sudsang.
CS 325 Computer Graphics 04 / 30 / 2010 Instructor: Michael Eckmann.
Monte Carlo Simulation of Folding Processes for 2D Linkages Modeling Proteins with Off-Grid HP-Chains Ileana Streinu Smith College Leo Guibas Rachel Kolodny.
11/25/03 3D Model Acquisition by Tracking 2D Wireframes Presenter: Jing Han Shiau M. Brown, T. Drummond and R. Cipolla Department of Engineering University.
CSCI480/582 Lecture 9 Chap.2.2 Cubic Splines – Hermit and Bezier Feb, 11, 2009.
Constructing Objects in Computer Graphics
Curve & Surface.
Types of Polygons Polygon- a flat closed figure made of straight line segments Circle the figures that are polygons. Cross out the figures 
that are.
CS 326A: Motion Planning Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces (1996) L. Kavraki, P. Švestka, J.-C. Latombe,
Constructing Objects in Computer Graphics By Andries van Dam©
Localizing the Delaunay Triangulation and its Parallel Implementation
Craig Schroeder October 26, 2004
Presentation transcript:

Part I: Linkages c: Locked Chains Joseph ORourke Smith College (Many slides made by Erik Demaine)

Outline zLocked Chains in 3D zLocked Trees in 2D zNo Locked Chains in 2D zAlgorithms for Unlocking Chains in 2D

Linkages / Frameworks zBar / link / edge = line segment zVertex / joint = connection between endpoints of bars Closed chain / cycle / polygon Open chain / arc TreeGeneral

Configurations zConfiguration = positions of the vertices that preserves the bar lengths Non-self-intersecting configurations Self-intersecting zNon-self-intersecting = No bars cross

Locked Question zCan a linkage be moved between any two non-self-intersecting configurations? ? zCan any non-self-intersecting configuration be unfolded, i.e., moved to canonical configuration? yEquivalent by reversing and concatenating motions

Canonical Configurations zArcs: Straight configuration zCycles: Convex configurations zTrees: Flat configurations

What Linkages Can Lock? [Schanuel & Bergman, early 1970s; Grenander 1987; Lenhart & Whitesides 1991; Mitchell 1992] zCan every chain be straightened? zCan every cycle be convexified? zCan every tree be flattened? ChainsCyclesTrees 2DYes No 3DNo 4D & higher Yes

Locked 3D Chains [Cantarella & Johnston 1998; Biedl, Demaine, Demaine, Lazard, Lubiw, ORourke, Overmars, Robbins, Streinu, Toussaint, Whitesides 1999] zCannot straighten some chains zIdea of proof: yEnds must be far away from the turns yTurns must stay relatively close to each other y Could effectively connect ends together yHence, any straightening unties a trefoil knot Sphere separates turns from ends

Locked 3D Chains [Cantarella & Johnston 1998; Biedl, Demaine, Demaine, Lazard, Lubiw, ORourke, Overmars, Robbins, Streinu, Toussaint, Whitesides 1999] zDouble this chain: zThis unknotted cycle cannot be convexified by the same argument zSeveral locked hexagons are also known Cantarella & Johnston 1998 Toussaint 1999

Locked 2D Trees [Biedl, Demaine, Demaine, Lazard, Lubiw, ORourke, Robbins, Streinu, Toussaint, Whitesides 1998] zTheorem: Not all trees can be flattened yNo petal can be opened unless all others are closed significantly yNo petal can be closed more than a little unless it has already opened

Converting the Tree into a Cycle zDouble each edge:

Converting the Tree into a Cycle zBut this cycle can be convexified:

Converting the Tree into a Cycle zBut this cycle can be convexified:

One Key Idea for 2D Cycles: Increasing Distances zA motion is expansive if no inter-vertex distances decreases zLemma: If a motion is expansive, the framework cannot cross itself

Theorem [Connelly, Demaine, Rote 2000] zFor any family of chains and cycles, there is a motion that yMakes the chains straight yMakes the cycles convex yIncreases most pairwise distances (and area) zExcept: Chains or cycles contained within a cycle might not be straightened or convexified zFurthermore: Motion preserves symmetries and is piecewise-differentiable (smooth)

Conclusion zConstructive proof that every polygonal chain can be straightened and every polygon can be convexified yBased on flow through a vector field defined implicitly by an optimization problem yNot technically a finite algorithm yEasy to approximate in practice yConsequences: xPiecewise-differentiable xPreserve symmetries of linkage xConfiguration space is contractible

Algorithms for 2D Chains Connelly, Demaine, Rote (2000) ODE + convex programming Streinu (2000) pseudotriangulations + piecewise-algebraic motions Cantarella, Demaine, Iben, OBrien (2003) energy

Energy Algorithm [Cantarella, Demaine, Iben, OBrien] zUse ideas from knot energies to evolve a linkage via gradient descent zLoosen expansiveness constraint; still avoid crossings zResulting motion is simpler yC (instead of piecewise-C 1 or piecewise-C ) yEasy to compute, even physically yIn polynomial time, produce simplest possible explicit representation: piecewise-linear yPreserves initial symmetries in the linkage

Basic Idea zDefine energy function on configurations so that yCrossing requires infinite energy yExpansive motions decrease energy yMinimum-energy configuration is straight/convex zFollow any energy-decreasing motion yGuaranteed to exist by expansive motion yNot necessarily expansive, but avoids crossings ySmooth (C ) motion preserving symmetries

Euclidean-Distance Energy zC 1,1 (Lipschitz) zCharge boundary) zRepulsive (expansive) zSeparable (components) Energy field applied to an additional point not on the white chain, ignoring nearest terms e v

Algorithm zParameterize to keep bars fixed length and cycles closed y(Cosines of) angles, except for some in cycles yCompute location of final vertex in cycle by intersecting two circles zCompute Euclidean gradient in O(n 2 ) time zFollow gradient linearly by a magnitude that decreases energy best zUse bounds on convergence of steepest descent θ1θ1 θ2θ2 θ3θ3 θ4θ4 θ5θ5 θ6θ6 θ7θ7 θ8θ8 θ9θ9

Visual Comparison CDR Energy CDR Energy

Energy Examples spiral spider tentacle

Energy Animations zhttp:// AED/index.htmlhttp:// AED/index.html zteeth.avi ztree.avi zdoubleSpiral.avi zspider.avi ztentacle.avi