Initialize Pose2 in a factor graph using LAGO (Linear Approximation for Graph Optimization). see papers: More...
#include <gtsam/nonlinear/NonlinearFactorGraph.h>#include <gtsam/linear/GaussianFactorGraph.h>#include <gtsam/linear/VectorValues.h>#include <gtsam/inference/graph.h>
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Namespaces | |
| gtsam | |
| traits | |
| gtsam::lago | |
Typedefs | |
| typedef std::map< Key, double > | gtsam::lago::key2doubleMap |
Functions | |
| GTSAM_EXPORT GaussianFactorGraph | gtsam::lago::buildLinearOrientationGraph (const std::vector< size_t > &spanningTreeIds, const std::vector< size_t > &chordsIds, const NonlinearFactorGraph &g, const key2doubleMap &orientationsToRoot, const PredecessorMap< Key > &tree) |
| key2doubleMap | gtsam::lago::computeThetasToRoot (const key2doubleMap &deltaThetaMap, const PredecessorMap< Key > &tree) |
| GTSAM_EXPORT void | gtsam::lago::getSymbolicGraph (std::vector< size_t > &spanningTreeIds, std::vector< size_t > &chordsIds, key2doubleMap &deltaThetaMap, const PredecessorMap< Key > &tree, const NonlinearFactorGraph &g) |
| Values | gtsam::lago::initialize (const NonlinearFactorGraph &graph, bool useOdometricPath) |
| Values | gtsam::lago::initialize (const NonlinearFactorGraph &graph, const Values &initialGuess) |
| VectorValues | gtsam::lago::initializeOrientations (const NonlinearFactorGraph &graph, bool useOdometricPath) |
Detailed Description
Initialize Pose2 in a factor graph using LAGO (Linear Approximation for Graph Optimization). see papers:
- Date
- May 14, 2014
L. Carlone, R. Aragues, J. Castellanos, and B. Bona, A fast and accurate approximation for planar pose graph optimization, IJRR, 2014.
L. Carlone, R. Aragues, J.A. Castellanos, and B. Bona, A linear approximation for graph-based simultaneous localization and mapping, RSS, 2011.
- Parameters
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graph nonlinear factor graph (can include arbitrary factors but we assume that there is a subgraph involving Pose2 and betweenFactors). Also in the current version we assume that there is an odometric spanning path (x0->x1, x1->x2, etc) and a prior on x0. This assumption can be relaxed by using the extra argument useOdometricPath = false, although this part of code is not stable yet.
- Returns
- Values: initial guess from LAGO (only pose2 are initialized)
- Date
- May 14, 2014
Definition in file lago.h.