5007439

SLAM: Localización de robots y construcción
simultánea de mapas

**SLAM simulator
for MatLab**

The **slam.m** program is a
simple SLAM simulation written in MatLab.
A mobile robot carries out a square trajectory in an environment with
point features at each side of the trajectory, similar to a cloister (see
figure below; red points and trajectory are ground truth):

The vehicle is equipped with a point detector whose characteristics
(range, precision) can be modified.
Vehicle odometry can also be modified.
You can also try different data association algorithms: the Nearest
Neighbour, the Joint Compatibility Branch and Bound, or your own!

- Load
**slam.m**, find where data association is done and try the nearest neighbour (**NN**) algorithm.

- Complete
**SINGLES**and try it:

You have **observations.m** observations, and **prediction.n** predicted features.

For every observation i,
check whether it has only one neighbour,

feature, and whether that
feature j has only that one neighbour

observation i. If so, **H(i) = j**.

You will need to check the **compatibility.ic** matrix

for this:

**compatibility.ic(i,j) = 1** if observation **i** is a neighbour of

feature **j**.

- Include
people (
**configuration.people = 1**) and try**SINGLES**

- Try Joint
Compatibility Branch and Bound (
**JCBB**)