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title = slam heading = Fundamentals of a SLAM Algorithm subheading = Discuss the basic concepts behind all SLAM Algorithms. category = Information tags = algorithm author = Arunabh Ghosh date = May 30, 2016 //(DO NOT REMOVE THESE LINES) //(WRITE YOUR BLOG BELOW FROM LINE 12)


The term SLAM is as stated an acronym for Simultaneous Localization And Mapping. Mapping is all about building maps of the environment. There are a number of different methods for building maps and some of them are quite sophisticated. All these methods have in common that they build a model of the environment while also addressing the fact that the robot itself accrues uncertainty while it moves.

Steps involved in SLAM Algorithms

The various algorithm consists of multiple parts; Landmark extraction, data association, state estimation, state update and landmark update. This post will explain what happens in each step. There are many different algorithms to accomplish each of these steps and one can follow any one of the methods. The fundamentals of each algorithm is what this post will explain.


After Landmark update the robot moves and then the whole cycle repeats again. When the robot moves the uncertainty of its position increases. After the cycle not only the robot is confident of its position but has also extracted information about the environment and associated itself with it. In this way the robot not only maps the environment but also knows where it is in it.


The main aim of this post was to familiarize one with the basics of a SLAM Algorithm to the level that he/she is now able to go further, read tutorials from the internet and implement a SLAM based robot. The applications of this technology are infinite. It is the key to self-driving cars, unmanned aerial vehicles, autonomous underwater vehicles, planetary rovers, newly emerging domestic robots and even robots inside the human body. It is a big and active research field with many unsolved problems.

Hope you had a good time reading this blog and were able to learn something new!!

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