Added SmartProjectionFactorExample_kitti.cpp.
Currently loads kitti dataset after processing by VO code (stereo_factors.txt and camera_poses.txt) Creates graph after N landmarks have been seen, runs it through SmartProjectionFactor Verification of output is still needed; LM seems to optimize but poses don't seem to change.release/4.3a0
Zsolt Kira
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/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file SmartProjectionFactorExample_kitti.cpp
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* @brief Example usage of SmartProjectionFactor using real dataset
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* @date August, 2013
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* @author Zsolt Kira
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*/
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// Both relative poses and recovered trajectory poses will be stored as Pose2 objects
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#include <gtsam/geometry/Pose3.h>
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// Each variable in the system (poses and landmarks) must be identified with a unique key.
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// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1).
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// Here we will use Symbols
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#include <gtsam/nonlinear/Symbol.h>
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// We want to use iSAM2 to solve the range-SLAM problem incrementally
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#include <gtsam/nonlinear/ISAM2.h>
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// iSAM2 requires as input a set set of new factors to be added stored in a factor graph,
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// and initial guesses for any new variables used in the added factors
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/Values.h>
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// We will use a non-liear solver to batch-inituialize from the first 150 frames
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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// In GTSAM, measurement functions are represented as 'factors'. Several common factors
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// have been provided with the library for solving robotics SLAM problems.
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#include <gtsam/slam/PriorFactor.h>
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#include <gtsam/slam/BetweenFactor.h>
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#include <gtsam_unstable/slam/SmartProjectionFactor.h>
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// Standard headers, added last, so we know headers above work on their own
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#include <boost/foreach.hpp>
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#include <fstream>
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#include <iostream>
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using namespace std;
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using namespace gtsam;
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namespace NM = gtsam::noiseModel;
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using symbol_shorthand::X;
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using symbol_shorthand::L;
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typedef PriorFactor<Pose3> Pose3Prior;
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static SharedNoiseModel prior_model(noiseModel::Diagonal::Sigmas(Vector_(6, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01)));
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/* ************************************************************************* */
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Values::shared_ptr loadPoseValues(const string& filename, list<Key> keys) {
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Values::shared_ptr values(new Values());
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std::list<Key>::iterator kit;
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// read in camera poses
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string full_filename = filename;
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ifstream fin;
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fin.open(full_filename.c_str());
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int pose_id;
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while (fin >> pose_id) {
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double pose_matrix[16];
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for (int i = 0; i < 16; i++) {
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fin >> pose_matrix[i];
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}
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kit = find (keys.begin(), keys.end(), X(pose_id));
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if (kit != keys.end()) {
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cout << " Adding " << X(pose_id) << endl;
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values->insert(Symbol('x',pose_id), Pose3(Matrix_(4, 4, pose_matrix)));
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}
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}
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fin.close();
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return values;
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}
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// main
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int main(int argc, char** argv) {
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string HOME = getenv("HOME");
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string input_dir = HOME + "/data/kitti/loop_closures_merged/";
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Cal3_S2::shared_ptr K(new Cal3_S2(718.856, 718.856, 0.0, 607.1928, 185.2157));
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typedef SmartProjectionFactor<Pose3, Point3, Cal3_S2> SmartFactor;
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// Read in kitti dataset
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// load stereo factors and initialize landmarks when first seen
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ifstream fin;
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fin.open((input_dir+"stereo_factors.txt").c_str());
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if(!fin) {
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cerr << "Could not open stereo_factors.txt" << endl;
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exit(1);
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}
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static SharedNoiseModel pixel_sigma(noiseModel::Unit::Create(3));
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static SharedNoiseModel prior_model(noiseModel::Diagonal::Sigmas(Vector_(6, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01)));
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NonlinearFactorGraph graph;
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// read all measurements tracked by VO
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cout << "Loading stereo_factors.txt" << endl;
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int count = 0;
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int currentLandmark = 0;
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int numLandmarks = 0;
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Key r, l;
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double uL, uR, v, x, y, z;
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std::list<Key> allViews;
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std::vector<Key> views;
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std::vector<Point2> measurements;
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Values values;
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bool updateGraph = false;
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while (fin >> r >> l >> uL >> uR >> v >> x >> y >> z) {
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cout << "CurrentLandmark " << currentLandmark << " Landmark " << l << std::endl;
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if (currentLandmark != l && views.size() < 3) {
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// New landmark. Not enough views for previous landmark so move on.
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cout << "New landmark " << l << " with not enough view for previous one" << std::endl;
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currentLandmark = l;
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views.clear();
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measurements.clear();
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} else if (currentLandmark != l) {
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// New landmark. Add previous landmark and associated views to new factor
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cout << "New landmark " << l << " with "<< views.size() << " views for previous landmark " << currentLandmark << std::endl;
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cout << "Keys ";
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BOOST_FOREACH(const Key& k, views) {
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allViews.push_back(k);
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cout << k << " ";
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}
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cout << endl;
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cout << "Measurements ";
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BOOST_FOREACH(const Point2& p, measurements) {
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cout << p << " ";
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}
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cout << endl;
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SmartFactor::shared_ptr smartFactor(new SmartFactor(measurements, pixel_sigma, views, K));
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numLandmarks++;
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graph.push_back(smartFactor);
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if (numLandmarks > 4) {
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updateGraph = true;
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}
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currentLandmark = l;
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views.clear();
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measurements.clear();
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} else {
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// We have new view for current landmark, so add it to the list later
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cout << "New view for landmark " << l << " (" << views.size() << " total)" << std::endl;
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}
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views += X(r);
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measurements += Point2(uL,v);
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// Optimize
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if (updateGraph) {
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cout << "Optimizing... " << endl;
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// Get all view in the graph and populate poses from VO output
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// TODO: Handle loop closures properly
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allViews.unique();
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cout << "All Keys ";
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values = *loadPoseValues(input_dir+"camera_poses.txt", allViews);
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BOOST_FOREACH(const Key& k, allViews) {
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cout << k << " ";
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}
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cout << endl;
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// Optimize!
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LevenbergMarquardtParams params;
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params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
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params.verbosity = NonlinearOptimizerParams::ERROR;
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Values result;
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gttic_(SmartProjectionFactorExample_kitti);
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LevenbergMarquardtOptimizer optimizer(graph, values, params);
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result = optimizer.optimize();
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gttoc_(SmartProjectionFactorExample_kitti);
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tictoc_finishedIteration_();
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values.print("before optimization ");
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result.print("results of kitti optimization ");
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tictoc_print_();
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updateGraph = false;
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values.clear();
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allViews.clear();
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graph = NonlinearFactorGraph();
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}
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count++;
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if(count==100000) {
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cout << "Loading graph... " << graph.size() << endl;
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count=0;
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}
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}
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cout << "Graph size: " << graph.size() << endl;
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exit(0);
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}
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