Merge pull request #1131 from borglab/fix/rangeISam

examples/RangeISAMExample_plaza2.cpp

@@ -10,62 +10,81 @@
  * -------------------------------------------------------------------------- */
 
 /**
- * @file RangeISAMExample_plaza1.cpp
+ * @file RangeISAMExample_plaza2.cpp
  * @brief A 2D Range SLAM example
  * @date June 20, 2013
- * @author FRank Dellaert
+ * @author Frank Dellaert
  */
 
-// Both relative poses and recovered trajectory poses will be stored as Pose2 objects
+// Both relative poses and recovered trajectory poses will be stored as Pose2.
 #include <gtsam/geometry/Pose2.h>
+using gtsam::Pose2;
 
-// Each variable in the system (poses and landmarks) must be identified with a unique key.
+// gtsam::Vectors are dynamic Eigen vectors, Vector3 is statically sized.
-// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1).
+#include <gtsam/base/Vector.h>
-// Here we will use Symbols
+using gtsam::Vector;
+using gtsam::Vector3;
+
+// Unknown landmarks are of type Point2 (which is just a 2D Eigen vector).
+#include <gtsam/geometry/Point2.h>
+using gtsam::Point2;
+
+// Each variable in the system (poses and landmarks) must be identified with a
+// unique key. We can either use simple integer keys (1, 2, 3, ...) or symbols
+// (X1, X2, L1). Here we will use Symbols.
 #include <gtsam/inference/Symbol.h>
+using gtsam::Symbol;
 
-// We want to use iSAM2 to solve the range-SLAM problem incrementally
+// We want to use iSAM2 to solve the range-SLAM problem incrementally.
 #include <gtsam/nonlinear/ISAM2.h>
 
-// iSAM2 requires as input a set set of new factors to be added stored in a factor graph,
+// iSAM2 requires as input a set set of new factors to be added stored in a
-// and initial guesses for any new variables used in the added factors
+// factor graph, and initial guesses for any new variables in the added factors.
 #include <gtsam/nonlinear/NonlinearFactorGraph.h>
 #include <gtsam/nonlinear/Values.h>
 
-// We will use a non-liear solver to batch-inituialize from the first 150 frames
+// We will use a non-linear solver to batch-initialize from the first 150 frames
 #include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
 
-// In GTSAM, measurement functions are represented as 'factors'. Several common factors
+// Measurement functions are represented as 'factors'. Several common factors
-// have been provided with the library for solving robotics SLAM problems.
+// have been provided with the library for solving robotics SLAM problems:
-#include <gtsam/slam/BetweenFactor.h>
 #include <gtsam/sam/RangeFactor.h>
+#include <gtsam/slam/BetweenFactor.h>
 #include <gtsam/slam/dataset.h>
 
-// Standard headers, added last, so we know headers above work on their own
+// Timing, with functions below, provides nice facilities to benchmark.
+#include <gtsam/base/timing.h>
+using gtsam::tictoc_print_;
+
+// Standard headers, added last, so we know headers above work on their own.
 #include <fstream>
 #include <iostream>
+#include <random>
+#include <set>
+#include <string>
+#include <utility>
+#include <vector>
 
-using namespace std;
-using namespace gtsam;
 namespace NM = gtsam::noiseModel;
 
-// data available at http://www.frc.ri.cmu.edu/projects/emergencyresponse/RangeData/
+// Data is second UWB ranging dataset, B2 or "plaza 2", from
-// Datafile format (from http://www.frc.ri.cmu.edu/projects/emergencyresponse/RangeData/log.html)
+// "Navigating with Ranging Radios: Five Data Sets with Ground Truth"
+// by Joseph Djugash, Bradley Hamner, and Stephan Roth
+// https://www.ri.cmu.edu/pub_files/2009/9/Final_5datasetsRangingRadios.pdf
 
 // load the odometry
 // DR: Odometry Input (delta distance traveled and delta heading change)
-//    Time (sec)  Delta Dist. Trav. (m) Delta Heading (rad)
+//    Time (sec)  Delta Distance Traveled (m) Delta Heading (rad)
-typedef pair<double, Pose2> TimedOdometry;
+using TimedOdometry = std::pair<double, Pose2>;
-list<TimedOdometry> readOdometry() {
+std::list<TimedOdometry> readOdometry() {
-  list<TimedOdometry> odometryList;
+  std::list<TimedOdometry> odometryList;
-  string data_file = findExampleDataFile("Plaza2_DR.txt");
+  std::string data_file = gtsam::findExampleDataFile("Plaza2_DR.txt");
-  ifstream is(data_file.c_str());
+  std::ifstream is(data_file.c_str());
 
   while (is) {
     double t, distance_traveled, delta_heading;
     is >> t >> distance_traveled >> delta_heading;
-    odometryList.push_back(
+    odometryList.emplace_back(t, Pose2(distance_traveled, 0, delta_heading));
-        TimedOdometry(t, Pose2(distance_traveled, 0, delta_heading)));
   }
   is.clear(); /* clears the end-of-file and error flags */
   return odometryList;
@@ -73,17 +92,16 @@ list<TimedOdometry> readOdometry() {
 
 // load the ranges from TD
 //    Time (sec)  Sender / Antenna ID Receiver Node ID  Range (m)
-typedef boost::tuple<double, size_t, double> RangeTriple;
+using RangeTriple = boost::tuple<double, size_t, double>;
-vector<RangeTriple> readTriples() {
+std::vector<RangeTriple> readTriples() {
-  vector<RangeTriple> triples;
+  std::vector<RangeTriple> triples;
-  string data_file = findExampleDataFile("Plaza2_TD.txt");
+  std::string data_file = gtsam::findExampleDataFile("Plaza2_TD.txt");
-  ifstream is(data_file.c_str());
+  std::ifstream is(data_file.c_str());
 
   while (is) {
-    double t, sender, range;
+    double t, range, sender, receiver;
-    size_t receiver;
     is >> t >> sender >> receiver >> range;
-    triples.push_back(RangeTriple(t, receiver, range));
+    triples.emplace_back(t, receiver, range);
   }
   is.clear(); /* clears the end-of-file and error flags */
   return triples;
@@ -91,18 +109,19 @@ vector<RangeTriple> readTriples() {
 
 // main
 int main(int argc, char** argv) {
-
   // load Plaza2 data
-  list<TimedOdometry> odometry = readOdometry();
+  std::list<TimedOdometry> odometry = readOdometry();
-//  size_t M = odometry.size();
+  size_t M = odometry.size();
+  std::cout << "Read " << M << " odometry entries." << std::endl;
 
-  vector<RangeTriple> triples = readTriples();
+  std::vector<RangeTriple> triples = readTriples();
   size_t K = triples.size();
+  std::cout << "Read " << K << " range triples." << std::endl;
 
   // parameters
-  size_t minK = 150; // minimum number of range measurements to process initially
+  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
@@ -111,34 +130,28 @@ int main (int argc, char** argv) {
   double sigmaR = 100;        // range standard deviation
   const NM::Base::shared_ptr  // all same type
       priorNoise = NM::Diagonal::Sigmas(priorSigmas),  // prior
+      looseNoise = NM::Isotropic::Sigma(2, 1000),      // loose LM 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
+      tukey = NM::Robust::Create(NM::mEstimator::Tukey::Create(15),
+                                 gaussian),  // robust
       rangeNoise = robust ? tukey : gaussian;
 
   // Initialize iSAM
-  ISAM2 isam;
+  gtsam::ISAM2 isam;
 
   // Add prior on first pose
-  Pose2 pose0 = Pose2(-34.2086489999201, 45.3007639991120,
+  Pose2 pose0 = Pose2(-34.2086489999201, 45.3007639991120, M_PI - 2.021089);
-      M_PI - 2.02108900000000);
+  gtsam::NonlinearFactorGraph newFactors;
-  NonlinearFactorGraph newFactors;
   newFactors.addPrior(0, pose0, priorNoise);
-  Values initial;
+  gtsam::Values initial;
   initial.insert(0, pose0);
 
-  //  initialize points
+  // We will initialize landmarks randomly, and keep track of which landmarks we
-  if (groundTruth) { // from TL file
+  // already added with a set.
-    initial.insert(symbol('L', 1), Point2(-68.9265, 18.3778));
+  std::mt19937_64 rng;
-    initial.insert(symbol('L', 6), Point2(-37.5805, 69.2278));
+  std::normal_distribution<double> normal(0.0, 100.0);
-    initial.insert(symbol('L', 0), Point2(-33.6205, 26.9678));
+  std::set<Symbol> initializedLandmarks;
-    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
@@ -150,13 +163,14 @@ int main (int argc, char** argv) {
   // Loop over odometry
   gttic_(iSAM);
   for (const TimedOdometry& timedOdometry : odometry) {
-    //--------------------------------- odometry loop -----------------------------------------
+    //--------------------------------- odometry loop --------------------------
     double t;
     Pose2 odometry;
     boost::tie(t, odometry) = timedOdometry;
 
     // add odometry factor
-    newFactors.push_back(BetweenFactor<Pose2>(i-1, i, odometry, odoNoise));
+    newFactors.emplace_shared<gtsam::BetweenFactor<Pose2>>(i - 1, i, odometry,
+                                                           odoNoise);
 
     // predict pose and add as initial estimate
     Pose2 predictedPose = lastPose.compose(odometry);
@@ -166,8 +180,20 @@ int main (int argc, char** argv) {
     // 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]);
+      Symbol landmark_key('L', j);
       double range = boost::get<2>(triples[k]);
-      newFactors.push_back(RangeFactor<Pose2, Point2>(i, symbol('L', j), range,rangeNoise));
+      newFactors.emplace_shared<gtsam::RangeFactor<Pose2, Point2>>(
+          i, landmark_key, range, rangeNoise);
+      if (initializedLandmarks.count(landmark_key) == 0) {
+        std::cout << "adding landmark " << j << std::endl;
+        double x = normal(rng), y = normal(rng);
+        initial.insert(landmark_key, Point2(x, y));
+        initializedLandmarks.insert(landmark_key);
+        // We also add a very loose prior on the landmark in case there is only
+        // one sighting, which cannot fully determine the landmark.
+        newFactors.emplace_shared<gtsam::PriorFactor<Point2>>(
+            landmark_key, Point2(0, 0), looseNoise);
+      }
       k = k + 1;
       countK = countK + 1;
     }
@@ -175,8 +201,9 @@ int main (int argc, char** argv) {
     // Check whether to update iSAM 2
     if ((k > minK) && (countK > incK)) {
       if (!initialized) {  // Do a full optimize for first minK ranges
+        std::cout << "Initializing at time " << k << std::endl;
         gttic_(batchInitialization);
-        LevenbergMarquardtOptimizer batchOptimizer(newFactors, initial);
+        gtsam::LevenbergMarquardtOptimizer batchOptimizer(newFactors, initial);
         initial = batchOptimizer.optimize();
         gttoc_(batchInitialization);
         initialized = true;
@@ -185,21 +212,27 @@ int main (int argc, char** argv) {
       isam.update(newFactors, initial);
       gttoc_(update);
       gttic_(calculateEstimate);
-      Values result = isam.calculateEstimate();
+      gtsam::Values result = isam.calculateEstimate();
       gttoc_(calculateEstimate);
       lastPose = result.at<Pose2>(i);
-      newFactors = NonlinearFactorGraph();
+      newFactors = gtsam::NonlinearFactorGraph();
-      initial = Values();
+      initial = gtsam::Values();
       countK = 0;
     }
     i += 1;
-    //--------------------------------- odometry loop -----------------------------------------
+    //--------------------------------- odometry loop --------------------------
   }  // end for
   gttoc_(iSAM);
 
   // Print timings
   tictoc_print_();
 
-  exit(0);
+  // Print optimized landmarks:
+  gtsam::Values finalResult = isam.calculateEstimate();
+  for (auto&& landmark_key : initializedLandmarks) {
+    Point2 p = finalResult.at<Point2>(landmark_key);
+    std::cout << landmark_key << ":" << p.transpose() << "\n";
   }
 
+  exit(0);
+}