# ekfSLAM

Perform simultaneous localization and mapping using extended Kalman filter

## Description

The `ekfSLAM`

object performs simultaneous localization and mapping
(SLAM) using an extended Kalman filter (EKF). It takes in observed landmarks from the
environment and compares them with known landmarks to find associations and new landmarks. Use
the associations to correct the state and state covariance. The new landmarks are augmented in
the state vector.

## Creation

### Syntax

### Description

creates an EKF SLAM object
with default properties.`slamObj`

= ekfSLAM

sets properties using one or more name-value pair arguments in addition to any combination
of input arguments from previous syntaxes. Any unspecified properties have default
values.`slamObj`

= ekfSLAM(`Name,Value`

)

specifies an upper bound on the number of landmarks `slamObj`

= ekfSLAM(`'MaxNumLandmark'`

,N,`Name,Value`

)`N`

allowed in the
state vector when generating code. This limit on the number of landmarks applies only when
generating code.

specifies the maximum size of the pose history `slamObj`

= ekfSLAM(`'MaxNumLandmark'`

,N,`‘MaxNumPoseStored’`

,M,`Name,Value`

)`M`

along with the maximum
number of landmarks `N`

in the state vector while generating code. These
limits apply only when generating code.

## Properties

## Object Functions

`copy` | Create deep copy of EKF SLAM object |

`correct` | Correct state and state error covariance |

`landmarkInfo` | Retrieve landmark information |

`poseHistory` | Retrieve corrected and predicted pose history |

`predict` | Predict state and state error covariance |

`removeLandmark` | Remove landmark from state vector |

`reset` | Reset state and state estimation error covariance |

## Examples

## Extended Capabilities

## See Also

### Objects

### Functions

`copy`

|`correct`

|`landmarkInfo`

|`poseHistory`

|`predict`

|`removeLandmark`

|`reset`

### Topics

**Introduced in R2021b**