82 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			C++
		
	
	
			
		
		
	
	
			82 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			C++
		
	
	
| /* ----------------------------------------------------------------------------
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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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| 
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|  * See LICENSE for the license information
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| 
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|  * -------------------------------------------------------------------------- */
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| 
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| /**
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|  * @file Pose3Localization.cpp
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|  * @brief A 3D Pose SLAM example that reads input from g2o, and initializes the Pose3 using InitializePose3
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|  * Syntax for the script is ./Pose3Localization input.g2o output.g2o
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|  * @date Aug 25, 2014
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|  * @author Luca Carlone
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|  */
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| 
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| #include <gtsam/slam/dataset.h>
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| #include <gtsam/slam/BetweenFactor.h>
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| #include <gtsam/nonlinear/GaussNewtonOptimizer.h>
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| #include <gtsam/nonlinear/Marginals.h>
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| #include <fstream>
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| 
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| using namespace std;
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| using namespace gtsam;
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| 
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| int main(const int argc, const char* argv[]) {
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|   // Read graph from file
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|   string g2oFile;
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|   if (argc < 2)
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|     g2oFile = findExampleDataFile("pose3Localizationexample.txt");
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|   else
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|     g2oFile = argv[1];
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| 
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|   NonlinearFactorGraph::shared_ptr graph;
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|   Values::shared_ptr initial;
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|   bool is3D = true;
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|   std::tie(graph, initial) = readG2o(g2oFile, is3D);
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| 
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|   // Add prior on the first key
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|   auto priorModel = noiseModel::Diagonal::Variances(
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|       (Vector(6) << 1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4).finished());
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|   Key firstKey = 0;
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|   for (const auto key : initial->keys()) {
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|     std::cout << "Adding prior to g2o file " << std::endl;
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|     firstKey = key;
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|     graph->addPrior(firstKey, Pose3(), priorModel);
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|     break;
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|   }
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| 
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|   std::cout << "Optimizing the factor graph" << std::endl;
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|   GaussNewtonParams params;
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|   params.setVerbosity("TERMINATION");  // show info about stopping conditions
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|   GaussNewtonOptimizer optimizer(*graph, *initial, params);
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|   Values result = optimizer.optimize();
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|   std::cout << "Optimization complete" << std::endl;
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| 
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|   std::cout << "initial error=" << graph->error(*initial) << std::endl;
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|   std::cout << "final error=" << graph->error(result) << std::endl;
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| 
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|   if (argc < 3) {
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|     result.print("result");
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|   } else {
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|     const string outputFile = argv[2];
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|     std::cout << "Writing results to file: " << outputFile << std::endl;
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|     NonlinearFactorGraph::shared_ptr graphNoKernel;
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|     Values::shared_ptr initial2;
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|     std::tie(graphNoKernel, initial2) = readG2o(g2oFile);
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|     writeG2o(*graphNoKernel, result, outputFile);
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|     std::cout << "done! " << std::endl;
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|   }
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| 
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|   // Calculate and print marginal covariances for all variables
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|   Marginals marginals(*graph, result);
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|   for (const auto& [key, pose] : result.extract<Pose3>()) {
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|     std::cout << marginals.marginalCovariance(key) << endl;
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|   }
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|   return 0;
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| }
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