Difference between revisions of "Constructive solid geometry"
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= Why functional representation is desirable = | = Why functional representation is desirable = | ||
− | + | Functional representation (representibg vvolumes with an implicit function in three variables) is especially suitable for CSG.<br> | |
− | + | Functional representation (F-Rep) | |
+ | * is typically more robust than boundary representation (B-Rep) | ||
+ | * is resolution preserving, and | ||
+ | * the boolean operations can be combined with [[blending operations]] with a simple change in math. | ||
== Pro: Higher robustness == | == Pro: Higher robustness == |
Revision as of 13:21, 13 July 2021
Constructive solid geometry (CSG) is a form of volumetric modelling where complex geometries can be built up
by combining simple geometries via boolean functions.
Contents
Why functional representation is desirable
Functional representation (representibg vvolumes with an implicit function in three variables) is especially suitable for CSG.
Functional representation (F-Rep)
- is typically more robust than boundary representation (B-Rep)
- is resolution preserving, and
- the boolean operations can be combined with blending operations with a simple change in math.
Pro: Higher robustness
Functional representation is typically more robust than a triangulation based boundary representation.
There is no need to worry about
- holes in meshes (meshes being not "watertight")
- flipped normals, degenerate triangles, coaxial edges, and
- a gazillion of other possible bad configurations.
Con: No convex hulls (general case)
Functional representation has one major weakness though:
The extremely useful of creating convex hulls seems not implementable (aside from a few special cases maybe)
F-Rep higher level than (polygonal modelling) B-Rep
Functional representation (F-Rep) is on a higher abstraction level than triangulation based boundary representation (B-Rep). That is
- F-Rep can be triamgulized to B-Rep to arbitrary precision
- Going from B-Rep to F-rep requires a bit of artistic creativity filling in the blanks
The relation between F-rep and polygonal modelling B-rep is respectively a bit like:
- the relation between vectrographics and rastergraphics
- the relation between Denotative continuous-time programming and treaton dtme in a discrete way
In all three cases dragging out the discretionary step to the last possible moment is the way to go.
Manipulation of the continuous not jet discreticed representations allows for more expressiveness and
even more importantly more scalability in the complexity of systems modelled.
Why signed distance functions are desirable
Functional representations with their scalar field (f(x,y,z) in R3 aka "algebraic variety")
being constrained to a norm of one can be useful. <vb>
(a special case with magnitude of gradient always being one - and C0 continuity?)
Finding points on the surfaces (by some root finding algorithm like Newton method or Regula falsi) can be much faster (one step).
That is useful for:
- Faster triangulation
- Ray marching
As an example:
- y^2 + y^2 + z^2 < R^2 – evaluated without taking toots suffices to define a sphere
- sqrt(y^2 + y^2 + z^2) < R – evaluated this way unlocks the power of SDFs at the cost of needing to compute a root
F-Rep basics
Only a few types of elements are essential for F-Rep CSG
- The base volumes
- The boolean operations for combining them
- The coordinate transformations
- (projections)
For a convex hull over any geometry it seems
it is unavoidable to leave F-Rep and triangulate down to B-Rep
Base volumes
Volumes are defined just by implicit functions in 3 variables (f(x,y,z) in R3)
Boolean operations
Combining geometries via volumetric boolean operations amounts to simple mathematical operations
- minimum or maximum function corresponds to intersection and union (respectively or reverse respectively deepening if inside is positive
- multiplicative negation (commonly known as multiplication with minus one) turns a volumes inside out and vice versa – with that and the above one can construct differences
Coordinate transformations
- linear transfomations (translation, rotation, shear, mirror, boost) ...
- nonlinear transformations (waves, swirls, twists, ...)
F-Rep challenges
Term simplification with a CAS
When big numbers of base geometries are combined this can lead to a really big symbolic expression.
The whole 3D models geometry is represented as one single formula (no matter how big).
One might need to simplify these in one way or another to get to acceptable performance.
Unfortunately this requires a full on computer algebra system (CAS) something that is typically not present as library in todays programming languages
- The experiment in implementing "F-Rep CSG" in the sage computer algebra system ran into this problem:
See: miniSageCAD - Interestingly Christian Scahfmeisters work on spiroligomers turned up similar algebraic simplification challenges
Term pruning
With max and min some parts of of the formula can completely cancel out for the most part of the total volume that the model occupies.
Thus there should also be other ways to prune out parts of the expression to avoid their unnecessary evaluation (and remember these pruneouts).
- Binary space partitioning trees
- Octrees
- ...
Quadrics
Nice projections
Quadrics are a limited subset of algebraic varieties with some useful properties.
One of them is that projecting them to a lower dimension like 2D always yields nice formulas (2D quadrics).
Quadriculation
Quatrics may be usable for some non-trianle-based B-Rep. That is:
Maybe some king of "quarticulation" is possible, analogous to "triangulation" but adding continuity of the first derivative as additional boundary condition.
External links
- Solid modeling – 3D modeling
- Constructive solid modelling: Constructive solid geometry
- Function representation F-Rep
- Boundary representation B-Rep
- Polygonal modeling
Math:
- Ray marching and Volume ray casting