SLAM for Dummies – A Tutorial Approach to Simultaneous Localization and Mapping

Søren Riisgaard，Morten Rufus Blas
[ Link to MIT ]

　　The goal of this document is to give a tutorial introduction to the field of SLAM (Simultaneous Localization And Mapping) for mobile robots. There are numerous papers on the subject but for someone new in the field it will require many hours of research to understand many of the intricacies involved in implementing SLAM. The hope is thus to present the subject in a clear and concise manner while keeping the　prerequisites required to understand the document to a minimum. It should actually　be possible to sit down and implement basic SLAM after having read this paper.
　　SLAM can be implemented in many ways. First of all there is a huge amount of different hardware that can be used. Secondly SLAM is more like a concept than a single algorithm. There are many steps involved in SLAM and these different steps can be implemented using a number of different algorithms. In most cases we explain a single approach to these different steps but hint at other possible ways to do them for the purpose of further reading.
　　The motivation behind writing this paper is primarily to help ourselves understand SLAM better. One will always get a better knowledge of a subject by teaching it. Second of all most of the existing SLAM papers are very theoretic and primarily focus on innovations in small areas of SLAM, which of course is their purpose. The purpose of this paper is to be very practical and focus on a simple, basic SLAM algorithm that can be used as a starting point to get to know SLAM better. For people with some background knowledge in SLAM we here present a complete solution for SLAM using EKF (Extended Kalman Filter). By complete we do not mean perfect. What we mean is that we cover all the basic steps required to get an implementation up and running. It must also be noted that SLAM as such has not been completely solved and there is still considerable research going on in the field.
　　To make it easy to get started all code is provided, so it is basically just a matter of downloading it, compiling it, plugging in the hardware (SICK laser scanner, ER1 robot) and executing the application; Plug-and-Play. We have used Microsoft Visual C# and the code will compile in the .Net Framework v. 1.1. Most of the code is very straightforward and can be read almost as pseudo-code, so porting to other languages or platforms should be easy.