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Frank Dellaert 2025-04-05 12:14:44 -04:00
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# Nonlinear
The `nonlinear` module in GTSAM focuses on solving nonlinear optimization problems using factor graphs and incremental solvers.
The `nonlinear` module in GTSAM includes a comprehensive set of tools for nonlinear optimization using factor graphs. Here's an overview of key components organized by category:
Key Concepts:
- **Nonlinear Factors**: Represent constraints or measurements in a nonlinear optimization problem.
- **Factor Graphs**: A graphical representation of the optimization problem.
- **Nonlinear Solvers**: Various optimization methods, typically calling linear solves in `linear`.
## Core Classes
## Basics
- **`NonlinearFactor.h`**: Defines the base classes for nonlinear factors, `NonlinearFactor` and `NoiseModelFactor`.
- **`NonlinearFactorGraph.h`**: Implements a factor graph consisting of nonlinear factors.
- **`Values.h`**: Stores variable assignments for optimization.
- **[NonlinearFactorGraph](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/NonlinearFactorGraph.h)**: Represents the optimization problem as a graph of factors.
- **[NonlinearFactor](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/NonlinearFactor.h)**: Base class for all nonlinear factors.
- **[NoiseModelFactor](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/NoiseModelFactor.h)**: Base class for factors with noise models.
- **[Values](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/Values.h)**: Container for variable assignments used in optimization.
## Optimizers:
- **`GaussNewtonOptimizer.h`**: Implements the Gauss-Newton optimization algorithm.
- **`LevenbergMarquardtOptimizer.h`**: Provides the Levenberg-Marquardt optimization algorithm.
- **`DoglegOptimizer.h`**: Implements the Dogleg optimization algorithm.
## Batch Optimizers
## Incremental Optimizers:
- **`ISAM2.h`**: Implements the iSAM2 incremental solver.
- **[NonlinearOptimizer](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/NonlinearOptimizer.h)**: Base class for all batch optimizers.
- **[NonlinearOptimizerParams](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/NonlinearOptimizerParams.h)**: Base parameters class for all optimizers.
- **[GaussNewtonOptimizer](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/GaussNewtonOptimizer.h)**: Implements Gauss-Newton optimization.
- **[GaussNewtonParams](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/GaussNewtonParams.h)**: Parameters for Gauss-Newton optimization.
- **[LevenbergMarquardtOptimizer](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/LevenbergMarquardtOptimizer.h)**: Implements Levenberg-Marquardt optimization.
- **[LevenbergMarquardtParams](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/LevenbergMarquardtParams.h)**: Parameters for Levenberg-Marquardt optimization.
- **[DoglegOptimizer](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/DoglegOptimizer.h)**: Implements Powell's Dogleg optimization.
- **[DoglegParams](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/DoglegParams.h)**: Parameters for Dogleg optimization.
- **[GncOptimizer](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/GncOptimizer.h)**: Implements robust optimization using Graduated Non-Convexity.
- **[GncParams](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/GncParams.h)**: Parameters for Graduated Non-Convexity optimization.
## Incremental Optimizers
- **[ISAM2](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/ISAM2.h)**: Incremental Smoothing and Mapping 2, with fluid relinearization.
- **[ISAM2Params](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/ISAM2Params.h)**: Parameters controlling the ISAM2 algorithm.
- **[ISAM2Result](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/ISAM2Result.h)**: Results from ISAM2 update operations.
- **[NonlinearISAM](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/NonlinearISAM.h)**: Original iSAM implementation (mostly superseded by ISAM2).
## Specialized Factors
- **[PriorFactor](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/PriorFactor.h)**: Imposes a prior constraint on a variable.
- **[NonlinearEquality](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/NonlinearEquality.h)**: Enforces equality constraints between variables.
- **[LinearContainerFactor](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/LinearContainerFactor.h)**: Wraps linear factors for inclusion in nonlinear factor graphs.
## Filtering and Smoothing
- **[ExtendedKalmanFilter](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/ExtendedKalmanFilter.h)**: Nonlinear Kalman filter implementation.
- **[FixedLagSmoother](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/FixedLagSmoother.h)**: Base class for fixed-lag smoothers.
- **[BatchFixedLagSmoother](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/BatchFixedLagSmoother.h)**: Implementation of a fixed-lag smoother using batch optimization.
## Analysis and Visualization
- **[Marginals](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/Marginals.h)**: Computes marginal covariances from optimization results.
- **[GraphvizFormatting](https://github.com/borglab/gtsam/blob/develop/gtsam/nonlinear/GraphvizFormatting.h)**: Provides customization for factor graph visualization.