本文整理汇总了C++中Pose2::compose方法的典型用法代码示例。如果您正苦于以下问题：C++ Pose2::compose方法的具体用法？C++ Pose2::compose怎么用？C++ Pose2::compose使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Pose2的用法示例。
在下文中一共展示了Pose2::compose方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: main
// main
int main(int argc, char** argv) {
// load Plaza1 data
list<TimedOdometry> odometry = readOdometry();
// size_t M = odometry.size();
vector<RangeTriple> triples = readTriples();
size_t K = triples.size();
// parameters
size_t start = 220, end=3000;
size_t minK = 100; // first batch of smart factors
size_t incK = 50; // minimum number of range measurements to process after
bool robust = true;
bool smart = true;
// Set Noise parameters
Vector priorSigmas = Vector3(1, 1, M_PI);
Vector odoSigmas = Vector3(0.05, 0.01, 0.2);
double sigmaR = 100; // range standard deviation
const NM::Base::shared_ptr // all same type
priorNoise = NM::Diagonal::Sigmas(priorSigmas), //prior
odoNoise = NM::Diagonal::Sigmas(odoSigmas), // odometry
gaussian = NM::Isotropic::Sigma(1, sigmaR), // non-robust
tukey = NM::Robust::Create(NM::mEstimator::Tukey::Create(15), gaussian), //robust
rangeNoise = robust ? tukey : gaussian;
// Initialize iSAM
ISAM2 isam;
// Add prior on first pose
Pose2 pose0 = Pose2(-34.2086489999201, 45.3007639991120,
M_PI - 2.02108900000000);
NonlinearFactorGraph newFactors;
newFactors.push_back(PriorFactor<Pose2>(0, pose0, priorNoise));
ofstream os2(
"/Users/dellaert/borg/gtsam/gtsam_unstable/examples/rangeResultLM.txt");
ofstream os3(
"/Users/dellaert/borg/gtsam/gtsam_unstable/examples/rangeResultSR.txt");
// initialize points (Gaussian)
Values initial;
if (!smart) {
initial.insert(symbol('L', 1), Point2(-68.9265, 18.3778));
initial.insert(symbol('L', 6), Point2(-37.5805, 69.2278));
initial.insert(symbol('L', 0), Point2(-33.6205, 26.9678));
initial.insert(symbol('L', 5), Point2(1.7095, -5.8122));
}
Values landmarkEstimates = initial; // copy landmarks
initial.insert(0, pose0);
// initialize smart range factors
size_t ids[] = { 1, 6, 0, 5 };
typedef boost::shared_ptr<SmartRangeFactor> SmartPtr;
map<size_t, SmartPtr> smartFactors;
if (smart) {
for(size_t jj: ids) {
smartFactors[jj] = SmartPtr(new SmartRangeFactor(sigmaR));
newFactors.push_back(smartFactors[jj]);
}
}
// set some loop variables
size_t i = 1; // step counter
size_t k = 0; // range measurement counter
Pose2 lastPose = pose0;
size_t countK = 0, totalCount=0;
// Loop over odometry
gttic_(iSAM);
for(const TimedOdometry& timedOdometry: odometry) {
//--------------------------------- odometry loop -----------------------------------------
double t;
Pose2 odometry;
boost::tie(t, odometry) = timedOdometry;
// add odometry factor
newFactors.push_back(
BetweenFactor<Pose2>(i - 1, i, odometry,
NM::Diagonal::Sigmas(odoSigmas)));
// predict pose and add as initial estimate
Pose2 predictedPose = lastPose.compose(odometry);
lastPose = predictedPose;
initial.insert(i, predictedPose);
landmarkEstimates.insert(i, predictedPose);
// Check if there are range factors to be added
while (k < K && t >= boost::get<0>(triples[k])) {
size_t j = boost::get<1>(triples[k]);
double range = boost::get<2>(triples[k]);
if (i > start) {
if (smart && totalCount < minK) {
smartFactors[j]->addRange(i, range);
printf("adding range %g for %d on %d",range,(int)j,(int)i);cout << endl;
}
else {
RangeFactor<Pose2, Point2> factor(i, symbol('L', j), range,
//.........这里部分代码省略.........
示例2: main
// main
int main (int argc, char** argv) {
// load Plaza2 data
list<TimedOdometry> odometry = readOdometry();
// size_t M = odometry.size();
vector<RangeTriple> triples = readTriples();
size_t K = triples.size();
// parameters
size_t minK = 150; // minimum number of range measurements to process initially
size_t incK = 25; // minimum number of range measurements to process after
bool groundTruth = false;
bool robust = true;
// Set Noise parameters
Vector priorSigmas = Vector3(1,1,M_PI);
Vector odoSigmas = Vector3(0.05, 0.01, 0.2);
double sigmaR = 100; // range standard deviation
const NM::Base::shared_ptr // all same type
priorNoise = NM::Diagonal::Sigmas(priorSigmas), //prior
odoNoise = NM::Diagonal::Sigmas(odoSigmas), // odometry
gaussian = NM::Isotropic::Sigma(1, sigmaR), // non-robust
tukey = NM::Robust::Create(NM::mEstimator::Tukey::Create(15), gaussian), //robust
rangeNoise = robust ? tukey : gaussian;
// Initialize iSAM
ISAM2 isam;
// Add prior on first pose
Pose2 pose0 = Pose2(-34.2086489999201, 45.3007639991120,
M_PI - 2.02108900000000);
NonlinearFactorGraph newFactors;
newFactors.push_back(PriorFactor<Pose2>(0, pose0, priorNoise));
Values initial;
initial.insert(0, pose0);
// initialize points
if (groundTruth) { // from TL file
initial.insert(symbol('L', 1), Point2(-68.9265, 18.3778));
initial.insert(symbol('L', 6), Point2(-37.5805, 69.2278));
initial.insert(symbol('L', 0), Point2(-33.6205, 26.9678));
initial.insert(symbol('L', 5), Point2(1.7095, -5.8122));
} else { // drawn from sigma=1 Gaussian in matlab version
initial.insert(symbol('L', 1), Point2(3.5784, 2.76944));
initial.insert(symbol('L', 6), Point2(-1.34989, 3.03492));
initial.insert(symbol('L', 0), Point2(0.725404, -0.0630549));
initial.insert(symbol('L', 5), Point2(0.714743, -0.204966));
}
// set some loop variables
size_t i = 1; // step counter
size_t k = 0; // range measurement counter
bool initialized = false;
Pose2 lastPose = pose0;
size_t countK = 0;
// Loop over odometry
gttic_(iSAM);
BOOST_FOREACH(const TimedOdometry& timedOdometry, odometry) {
//--------------------------------- odometry loop -----------------------------------------
double t;
Pose2 odometry;
boost::tie(t, odometry) = timedOdometry;
// add odometry factor
newFactors.push_back(BetweenFactor<Pose2>(i-1, i, odometry,NM::Diagonal::Sigmas(odoSigmas)));
// predict pose and add as initial estimate
Pose2 predictedPose = lastPose.compose(odometry);
lastPose = predictedPose;
initial.insert(i, predictedPose);
// Check if there are range factors to be added
while (k < K && t >= boost::get<0>(triples[k])) {
size_t j = boost::get<1>(triples[k]);
double range = boost::get<2>(triples[k]);
newFactors.push_back(RangeFactor<Pose2, Point2>(i, symbol('L', j), range,rangeNoise));
k = k + 1;
countK = countK + 1;
}
// Check whether to update iSAM 2
if ((k > minK) && (countK > incK)) {
if (!initialized) { // Do a full optimize for first minK ranges
gttic_(batchInitialization);
LevenbergMarquardtOptimizer batchOptimizer(newFactors, initial);
initial = batchOptimizer.optimize();
gttoc_(batchInitialization);
initialized = true;
}
gttic_(update);
isam.update(newFactors, initial);
gttoc_(update);
gttic_(calculateEstimate);
Values result = isam.calculateEstimate();
gttoc_(calculateEstimate);
lastPose = result.at<Pose2>(i);
newFactors = NonlinearFactorGraph();
//.........这里部分代码省略.........