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New interconnection strategy

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This commit is contained in:
tamasmeszaros 2019-03-05 16:28:18 +01:00
parent c2d5a8d03b
commit 7552556998
4 changed files with 216 additions and 246 deletions
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2
src/libslic3r/SLA/SLASpatIndex.hpp
View file

@ -43,6 +43,8 @@ public:
// For testing
size_t size() const;
bool empty() const { return size() == 0; }
void foreach(std::function<void(const SpatElement& el)> fn);
};
}

342
src/libslic3r/SLA/SLASupportTree.cpp
View file

@ -377,6 +377,7 @@ struct Pillar {
double r = 1;
size_t steps = 0;
Vec3d endpoint;
double height = 0;
long id = -1;
@ -390,12 +391,12 @@ struct Pillar {
{
assert(steps > 0);
double h = jp(Z) - endp(Z);
if(h > 0) { // Endpoint is below the starting point
height = jp(Z) - endp(Z);
if(height > 0) { // Endpoint is below the starting point
// We just create a bridge geometry with the pillar parameters and
// move the data.
Contour3D body = cylinder(radius, h, st, endp);
Contour3D body = cylinder(radius, height, st, endp);
mesh.points.swap(body.points);
mesh.indices.swap(body.indices);
}
@ -410,6 +411,10 @@ struct Pillar {
{
}
Vec3d startpoint() const {
return {endpoint(X), endpoint(Y), endpoint(Z) + height};
}
void add_base(double height = 3, double radius = 2) {
if(height <= 0) return;
@ -419,23 +424,23 @@ struct Pillar {
if(radius < r ) radius = r;
double a = 2*PI/steps;
double z = endpoint(2) + height;
double z = endpoint(Z) + height;
for(size_t i = 0; i < steps; ++i) {
double phi = i*a;
double x = endpoint(0) + r*std::cos(phi);
double y = endpoint(1) + r*std::sin(phi);
double x = endpoint(X) + r*std::cos(phi);
double y = endpoint(Y) + r*std::sin(phi);
base.points.emplace_back(x, y, z);
}
for(size_t i = 0; i < steps; ++i) {
double phi = i*a;
double x = endpoint(0) + radius*std::cos(phi);
double y = endpoint(1) + radius*std::sin(phi);
double x = endpoint(X) + radius*std::cos(phi);
double y = endpoint(Y) + radius*std::sin(phi);
base.points.emplace_back(x, y, z - height);
}
auto ep = endpoint; ep(2) += height;
auto ep = endpoint; ep(Z) += height;
base.points.emplace_back(endpoint);
base.points.emplace_back(ep);
@ -578,26 +583,15 @@ bool operator==(const SpatElement& e1, const SpatElement& e2) {
return e1.second == e2.second;
}
// Clustering a set of points by the given criteria.
ClusteredPoints cluster(
const PointSet& points, const std::vector<unsigned>& indices,
std::function<bool(const SpatElement&, const SpatElement&)> pred,
unsigned max_points = 0);
inline ClusteredPoints cluster(
const PointSet& points,
std::function<bool(const SpatElement&, const SpatElement&)> pred,
unsigned max_points = 0)
{
std::vector<unsigned> indices(size_t(points.rows()), 0);
std::iota(indices.begin(), indices.end(), 0);
return cluster(points, indices, pred, max_points);
}
ClusteredPoints cluster_nearest2d(
const PointSet& points, const std::vector<unsigned>& indices,
// Clustering a set of points by the given distance.
ClusteredPoints cluster(const std::vector<unsigned>& indices,
std::function<Vec3d(unsigned)> pointfn,
double dist,
unsigned max_points = 0);
unsigned max_points);
ClusteredPoints cluster(const PointSet& points,
double dist,
unsigned max_points);
// This class will hold the support tree meshes with some additional bookkeeping
// as well. Various parts of the support geometry are stored separately and are
@ -802,6 +796,8 @@ public:
};
// This function returns the position of the centroid in the input 'clust'
// vector of point indices.
template<class DistFn>
long cluster_centroid(const ClusterEl& clust,
std::function<Vec3d(size_t)> pointfn,
@ -1340,10 +1336,16 @@ class SLASupportTree::Algorithm {
// than we will bridge to this closer pillar
Vec3d qp(querypoint(X), querypoint(Y), gndlvl);
auto ne = spindex.nearest(qp, 1).front();
const Head& nearhead = m_result.head(ne.second);
auto qres = spindex.nearest(qp, 1);
if(qres.empty()) continue;
auto ne = qres.front();
const Head& nearhead = m_result.head(ne.second);
Vec3d nearhead_jp = nearhead.junction_point();
// const Pillar& nearpillar = m_result.pillars()[ne.second];
// Vec3d nearhead_jp = nearpillar.startpoint();
double dist2d = distance(qp, ne.first);
// Bridge endpoint on the main pillar
@ -1412,6 +1414,149 @@ class SLASupportTree::Algorithm {
m_result.add_bridge(headjp, touchjp, r);
}
// Interconnection strategy. Pillars with height exceeding H1 will require
// at least one neighbor to connect with. Height exceeding H2 require two
// neighbors. A connection only counts if the height ratio is bigger
// than 20%
void connect_pillars_nearest(unsigned neighbors = 3,
double H1 = 4.0, // min 1 neighbor required
double H2 = 35.0, // min 2 neighbor required
double min_height_ratio = 0.2)
{
// Now comes the algorithm that connects ground pillars with each other.
// Ideally every pillar should be connected with at least one of its
// neighbors if that neighbor is within sufficient distance (a bridge to
// it would not be longer than max_bridge_distance)
double d = std::cos(m_cfg.bridge_slope) * m_cfg.max_bridge_length_mm;
std::set<unsigned long> pairs;
m_pillar_index.foreach(
[this, d, &pairs, neighbors, min_height_ratio, H1, H2]
(const SpatElement& el)
{
Vec3d qp = el.first;
// Query all remaining points within reach
auto qres = m_pillar_index.query([qp, d](const SpatElement& e){
return distance(e.first, qp) < d;
});
// sort the result by distance (have to check if this is needed)
std::sort(qres.begin(), qres.end(),
[qp](const SpatElement& e1, const SpatElement& e2){
return distance(e1.first, qp) < distance(e2.first, qp);
});
const Pillar& pillar = m_result.head_pillar(el.second);
unsigned ncount = 0;
for(auto& re : qres) {
if(re.second == el.second) continue;
auto hashval = m_pillar_index.size() * el.second + re.second;
if(pairs.find(hashval) != pairs.end()) continue;
const Pillar& neighborpillar = m_result.head_pillar(re.second);
if(interconnect(pillar, neighborpillar)) {
pairs.insert(hashval);
// If the interconnection length between the two pillars is
// less than 20% of the longer pillar's height, don't count
if(std::min(pillar.height, neighborpillar.height) /
std::max(pillar.height, neighborpillar.height) >
min_height_ratio) ++ncount;
}
// 3 connections are enough for one pillar
if(ncount == neighbors) break;
}
if(ncount < 1 && pillar.height > H1) {
// No neighbors could be found and the pillar is too long.
BOOST_LOG_TRIVIAL(warning) << "Pillar is too long and has no "
"neighbors. Head ID: "
<< pillar.start_junction_id;
} else if(ncount < 2 && pillar.height > H2) {
// Not enough neighbors to support this pillar
BOOST_LOG_TRIVIAL(warning) << "Pillar is too long and has too "
"few neighbors. Head ID: "
<< pillar.start_junction_id;
}
});
}
// This is the old interconnection strategy which has a lot of imperfections
void connect_pillars_spiderweb() {
std::vector<unsigned> rem; rem.reserve(m_pillar_index.size());
std::vector<unsigned> ring;
// Could use an unordered_map instead. Points can be quite many.
std::vector<Vec2d> pts(size_t(m_points.rows()));
m_pillar_index.foreach([&rem, &pts](const SpatElement& e) {
rem.emplace_back(e.second);
pts[e.second] = {e.first(X), e.first(Y)};
});
while(!rem.empty()) { // loop until all the points belong to some ring
m_thr();
std::sort(rem.begin(), rem.end());
auto newring = pts_convex_hull(rem,
[&pts](unsigned i) {
return pts[i]; // project to 2D in along Z axis
});
if(!ring.empty()) {
// inner ring is now in 'newring' and outer ring is in 'ring'
SpatIndex innerring;
for(unsigned i : newring) { m_thr();
const Pillar& pill = m_result.head_pillar(i);
assert(pill.id >= 0);
innerring.insert(pill.endpoint, unsigned(pill.id));
}
// For all pillars in the outer ring find the closest in the
// inner ring and connect them. This will create the spider web
// fashioned connections between pillars
for(unsigned i : ring) { m_thr();
const Pillar& outerpill = m_result.head_pillar(i);
auto res = innerring.nearest(outerpill.endpoint,
unsigned(innerring.size()));
for(auto& ne : res) {
const Pillar& innerpill = m_result.pillars()[ne.second];
if(interconnect(outerpill, innerpill)) break;
}
}
}
// no need for newring anymore in the current iteration
ring.swap(newring);
// now the ring has to be connected with bridge sticks
for(auto it = ring.begin(), next = std::next(it);
next != ring.end();
++it, ++next)
{
m_thr();
const Pillar& pillar = m_result.head_pillar(*it);
const Pillar& nextpillar = m_result.head_pillar(*next);
interconnect(pillar, nextpillar);
}
auto sring = ring; ClusterEl tmp;
std::sort(sring.begin(), sring.end());
std::set_difference(rem.begin(), rem.end(),
sring.begin(), sring.end(),
std::back_inserter(tmp));
rem.swap(tmp);
}
}
public:
Algorithm(const SupportConfig& config,
@ -1450,11 +1595,7 @@ public:
void filter() {
// Get the points that are too close to each other and keep only the
// first one
auto aliases = cluster(m_points,
[this](const SpatElement& p, const SpatElement& se) {
m_thr();
return distance(p.first, se.first) < D_SP;
}, 2);
auto aliases = cluster(m_points, D_SP, 2);
PtIndices filtered_indices;
filtered_indices.reserve(aliases.size());
@ -1642,14 +1783,10 @@ public:
// These clusters of support points will join in one pillar,
// possibly in their centroid support point.
auto d_base = 2*m_cfg.base_radius_mm;
auto& thr = m_thr;
m_pillar_clusters = cluster(m_points, ground_head_indices,
[thr, d_base](const SpatElement& p, const SpatElement& s)
{
thr();
return distance(Vec2d(p.first(X), p.first(Y)),
Vec2d(s.first(X), s.first(Y))) < d_base;
}, 3); // max 3 heads to connect to one pillar
m_pillar_clusters = cluster(ground_head_indices,
[this](unsigned i) {
return m_points.row(i);
}, d_base, 3);
}
// Step: Routing the ground connected pinheads, and interconnecting
@ -1691,7 +1828,6 @@ public:
cl_centroids.push_back(unsigned(cid));
unsigned hid = cl[cid]; // Head ID
Head& h = m_result.head(hid);
h.transform();
@ -1705,8 +1841,7 @@ public:
size_t ci = 0;
for(auto cl : m_pillar_clusters) { m_thr();
auto cidx = cl_centroids[ci];
cl_centroids[ci++] = cl[cidx];
auto cidx = cl_centroids[ci++];
auto& head = m_result.head(cl[cidx]);
@ -1736,15 +1871,15 @@ public:
// at this point we either have our pillar index or we have
// to connect the sidehead to the ground
if(nearest_id < 0) {
Vec3d pend = Vec3d{sidehead_jp(X), sidehead_jp(Y), gndlvl};
// Could not find a pillar, create one
m_result.add_pillar(
unsigned(sidehead.id),
Vec3d{sidehead_jp(X), sidehead_jp(Y), gndlvl},
unsigned(sidehead.id), pend,
pradius).add_base(m_cfg.base_height_mm,
m_cfg.base_radius_mm);
// connects to ground, eligible for bridging
cl_centroids.emplace_back(c);
m_pillar_index.insert(pend, c);
} else {
// Creating the bridge to the nearest pillar
auto nearest_uid = unsigned(nearest_id);
@ -1754,113 +1889,9 @@ public:
}
}
// We will break down the pillar positions in 2D into concentric
// rings. Connecting the pillars belonging to the same ring will
// prevent bridges from crossing each other. After bridging the
// rings we can create bridges between the rings without the
// possibility of crossing bridges. Two pillars will be bridged
// with X shaped stick pairs. If they are really close to each
// other, than only one stick will be used in zig-zag mode.
// connect_pillars_spiderweb();
connect_pillars_nearest();
// Breaking down the points into rings will be done with a modified
// convex hull algorithm (see pts_convex_hull()), that works for
// collinear points as well. If the points are on the same surface,
// they can be part of an imaginary line segment for which the
// convex hull is not defined. I this case it is enough to sort the
// points spatially and create the bridge stick from one endpoint to
// another.
double d = std::cos(m_cfg.bridge_slope) * m_cfg.max_bridge_length_mm;
auto pclusters = cluster_nearest2d(m_points, cl_centroids, d, 3);
for(auto& ring : pclusters) {
// now the ring has to be connected with bridge sticks
if(ring.size() > 1)
for(auto it = ring.begin(), next = std::next(it);
next != ring.end();
++it, ++next)
{
m_thr();
const Pillar& pillar = m_result.head_pillar(*it);
const Pillar& nextpillar = m_result.head_pillar(*next);
interconnect(pillar, nextpillar);
}
if(ring.size() > 2) {
const Pillar& firstpillar = m_result.head_pillar(ring.front());
const Pillar& lastpillar = m_result.head_pillar(ring.back());
interconnect(firstpillar, lastpillar);
}
}
// ClusterEl rem = cl_centroids;
// ClusterEl ring;
// while(!rem.empty()) { // loop until all the points belong to some ring
// m_thr();
// std::sort(rem.begin(), rem.end());
// auto& points = m_points;
// auto newring = pts_convex_hull(rem,
// [&points](unsigned i) {
// auto&& p = points.row(i);
// return Vec2d(p(X), p(Y)); // project to 2D in along Z axis
// });
// if(!ring.empty()) {
// // inner ring is now in 'newring' and outer ring is in 'ring'
// SpatIndex innerring;
// for(unsigned i : newring) { m_thr();
// const Pillar& pill = m_result.head_pillar(i);
// assert(pill.id >= 0);
// innerring.insert(pill.endpoint, unsigned(pill.id));
// }
// // For all pillars in the outer ring find the closest in the
// // inner ring and connect them. This will create the spider web
// // fashioned connections between pillars
// for(unsigned i : ring) { m_thr();
// const Pillar& outerpill = m_result.head_pillar(i);
// auto res = innerring.nearest(outerpill.endpoint,
// unsigned(innerring.size()));
// for(auto& ne : res) {
// const Pillar& innerpill = m_result.pillars()[ne.second];
// if(interconnect(outerpill, innerpill)) break;
// }
// }
// }
// // no need for newring anymore in the current iteration
// ring.swap(newring);
// /*std::cout << "ring: \n";
// for(auto ri : ring) {
// std::cout << ri << " " << " X = " << gnd_head_pt(ri)(X)
// << " Y = " << gnd_head_pt(ri)(Y) << std::endl;
// }
// std::cout << std::endl;*/
// // now the ring has to be connected with bridge sticks
// for(auto it = ring.begin(), next = std::next(it);
// next != ring.end();
// ++it, ++next)
// {
// m_thr();
// const Pillar& pillar = m_result.head_pillar(*it);
// const Pillar& nextpillar = m_result.head_pillar(*next);
// interconnect(pillar, nextpillar);
// }
// auto sring = ring; ClusterEl tmp;
// std::sort(sring.begin(), sring.end());
// std::set_difference(rem.begin(), rem.end(),
// sring.begin(), sring.end(),
// std::back_inserter(tmp));
// rem.swap(tmp);
// }
}
// Step: routing the pinheads that would connect to the model surface
@ -1890,6 +1921,7 @@ public:
groundp(Z) = m_result.ground_level;
m_result.add_pillar(endp, groundp, head.r_back_mm).add_base(
m_cfg.base_height_mm, m_cfg.base_radius_mm);
// m_pillar_index.insert(groundp, unsigned(head.id));
};
// TODO: connect these to the ground pillars if possible

4
src/libslic3r/SLA/SLASupportTree.hpp
View file

@ -83,6 +83,10 @@ struct SupportConfig {
// The shortest distance of any support structure from the model surface
double safety_distance_mm = 0.1;
double max_solo_pillar_height_mm = 5.0;
double max_dual_pillar_height_mm = 35.0;
};
struct PoolConfig;

114
src/libslic3r/SLA/SLASupportTreeIGL.cpp
View file

@ -91,6 +91,11 @@ size_t SpatIndex::size() const
return m_impl->m_store.size();
}
void SpatIndex::foreach(std::function<void (const SpatElement &)> fn)
{
for(auto& el : m_impl->m_store) fn(el);
}
/* ****************************************************************************
* EigenMesh3D implementation
* ****************************************************************************/
@ -346,35 +351,11 @@ PointSet normals(const PointSet& points,
return ret;
}
namespace bgi = boost::geometry::index;
using Index3D = bgi::rtree< SpatElement, bgi::rstar<16, 4> /* ? */ >;
//template<class Vec> double distance(const Vec& p) {
// return std::sqrt(p.transpose() * p);
//}
//template<class Vec> double distance(const Vec& pp1, const Vec& pp2) {
// auto p = pp2 - pp1;
// return distance(p);
//}
// Clustering a set of points by the given criteria
ClusteredPoints cluster_nearest2d(
const sla::PointSet& points, const std::vector<unsigned>& indices,
double dist,
unsigned max_points = 0)
ClusteredPoints cluster(Index3D& sindex, double dist, unsigned max_points)
{
namespace bgi = boost::geometry::index;
using Index3D = bgi::rtree< SpatElement, bgi::rstar<16, 4> /* ? */ >;
// A spatial index for querying the nearest points
Index3D sindex;
// Build the index
for(unsigned idx : indices) {
Vec3d p = points.row(idx); p(Z) = 0;
sindex.insert( std::make_pair(points.row(idx), idx));
}
using Elems = std::vector<SpatElement>;
// Recursive function for visiting all the points in a given distance to
@ -438,79 +419,30 @@ ClusteredPoints cluster_nearest2d(
// Clustering a set of points by the given criteria
ClusteredPoints cluster(
const sla::PointSet& points, const std::vector<unsigned>& indices,
std::function<bool(const SpatElement&, const SpatElement&)> pred,
unsigned max_points = 0)
const std::vector<unsigned>& indices,
std::function<Vec3d(unsigned)> pointfn,
double dist,
unsigned max_points)
{
namespace bgi = boost::geometry::index;
using Index3D = bgi::rtree< SpatElement, bgi::rstar<16, 4> /* ? */ >;
// A spatial index for querying the nearest points
Index3D sindex;
// Build the index
for(unsigned idx : indices)
sindex.insert( std::make_pair(points.row(idx), idx));
for(auto idx : indices) sindex.insert( std::make_pair(pointfn(idx), idx));
using Elems = std::vector<SpatElement>;
return cluster(sindex, dist, max_points);
}
// Recursive function for visiting all the points in a given distance to
// each other
std::function<void(Elems&, Elems&)> group =
[&sindex, &group, pred, max_points](Elems& pts, Elems& cluster)
{
for(auto& p : pts) {
std::vector<SpatElement> tmp;
ClusteredPoints cluster(const PointSet& pts, double dist, unsigned max_points)
{
// A spatial index for querying the nearest points
Index3D sindex;
sindex.query(
bgi::satisfies([p, pred](const SpatElement& se) {
return pred(p, se);
}),
std::back_inserter(tmp)
);
// Build the index
for(Eigen::Index i = 0; i < pts.rows(); i++)
sindex.insert(std::make_pair(Vec3d(pts.row(i)), unsigned(i)));
auto cmp = [](const SpatElement& e1, const SpatElement& e2){
return e1.second < e2.second;
};
std::sort(tmp.begin(), tmp.end(), cmp);
Elems newpts;
std::set_difference(tmp.begin(), tmp.end(),
cluster.begin(), cluster.end(),
std::back_inserter(newpts), cmp);
int c = max_points && newpts.size() + cluster.size() > max_points?
int(max_points - cluster.size()) : int(newpts.size());
cluster.insert(cluster.end(), newpts.begin(), newpts.begin() + c);
std::sort(cluster.begin(), cluster.end(), cmp);
if(!newpts.empty() && (!max_points || cluster.size() < max_points))
group(newpts, cluster);
}
};
std::vector<Elems> clusters;
for(auto it = sindex.begin(); it != sindex.end();) {
Elems cluster = {};
Elems pts = {*it};
group(pts, cluster);
for(auto& c : cluster) sindex.remove(c);
it = sindex.begin();
clusters.emplace_back(cluster);
}
ClusteredPoints result;
for(auto& cluster : clusters) {
result.emplace_back();
for(auto c : cluster) result.back().emplace_back(c.second);
}
return result;
return cluster(sindex, dist, max_points);
}
}