SLAM for Robots

Updated: Feb 28

❓ Did you know that the first general-purpose #mobilerobot ‘Shakey the Robot’ was developed in 1972, almost half a century ago?!

🤖 Mobile robots can be distinguished from other robots by their ability to move autonomously (in an industrial plant, laboratory, planetary surface, etc.).

🧭 Various capabilities are required to enable a mobile robot to move in the real world to fulfill its objectives without human interaction. One of the most challenging, but a fundamental capability that mobile robots need is #navigation.

✨There are four building blocks of navigation - perception, localization, cognition, and motion control.

⛳️ Of these four components, #localization is considered one of the most elemental competencies. But why is it important? Because a robot needs to know where it is, and it needs to be able to make a plan for reaching a goal destination.

🗺 Simultaneous Localization And Mapping abbreviated as #SLAM, is the process by which a robot can build a map of an unknown environment and at the same time use this map to compute its own position and orientation.

🐣The chicken-or-egg problem - Starting with neither a map nor a location, both localization and mapping need to be done simultaneously to get an updated location of the robot as well as an updated estimate of the map.

❓ Why do we need SLAM? In environments such as indoors, underground, or underwater, where GPS signals are not available, a mobile agent has to rely solely on its onboard sensors to construct a representation of the environment to localize itself. Even in situations where GPS can provide coarse absolute position, SLAM can be used to provide a fine-grained location estimate of the robot.

✨To learn more about SLAM for #robotics, here are some interesting links:

An amazing lecture series to kick-start with the basics of SLAM


A survey paper of existing SLAM techniques


Contributing Editor: Kashmira Shinde


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