Diversity Associates Ltd.

Grid Slam Explorer

Note:This is a preview release. The final release will be more intuitive and less technical. 


This is a test application that lets you explore the Grid SLAM algorythm. It allows you to vary the number, position, orientation and interpretation of a number of range sensors of different types to see how the grid slam algorythm can help reduce uncertainty in mapping.

This version is an early release for feedback purposes. If you would like to contribute to the project, have feedback or have strong feelings about whether this should become open source or not, please get in touch.


Main Screen

This screen is the meat of the application, the rest are support screens for configuration.


Here you can alter the robot's max speed and change the cone model. The 'spray' of sonar cones can clearly be seen. It also lets you explore an obstacle avoidance algorythm based on minimum deviation from the current path and minumum turn sharpness. Currently this algorythm in not used in the rest of the app.

Motion Model

This lets you tweak the parameters of the motion model to choose an ammount of noise appropriate for your tests.

Beam Model

The beam model is used to calculate the correspondance between the expected reading and the real reading. To prevent over confidence it is usual to include quite a large amount of randomness.

Cone Model

This defines how new information is added to each particle's map. Future versions will allow for standard types (IR, Sonars, laser) and allow custom configuration on a per-sensor basis.


Currently the Vector Field Histogram algorythm is being used. At each step a VFH is made from the current best particle's map and the existing direction is altered so as to follow a 'valley' closest to the desired direction while keeping a distance from the walls.


When the app loads, click 'Do SLAM' and you should get an animation similar to this.

Things to try:


If you would like to test it on your hardware before a public release, please get in touch. chris@diversity.co.uk


Many thanks to all the great researchers who publish their work in an open manner. Inspiring papers include:

Many thanks also to Trevor Taylor for his feedback.


Please remember that this is an early release for feedback purposes and there are many improvements to be made.

Download: DiversityGridSlam_0.5.zip