Comparative Study on Autonomous Robot Trajectory Determination in an Unknown Indoor Environment
Comparative Study on Autonomous Robot Trajectory Determination in an Unknown Indoor Environment
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In this paper is presented a comparative study between using extended Kalman filter and particle filter applied on SLAM algorithm for an autonomous mobile robot. The robot navigates through an unknown indoor environment in which are placed 80 landmarks and it creates the map of the environment. Because the sensors placed on the robots produce measurement errors it is necessary to use Bayesian filters as the Kalman filter or the particle filter. An application was implemented that shows the estimated measurement errors produced while using both filters in order to create the estimated map of the closed environment in which the autonomous mobile robot is navigating.
Document information
Comparative Study on Autonomous Robot Trajectory Determination in an Unknown Indoor Environment
Applied Mechanics and Materials ; 555 ; 327-333
2014-06-30
7 pages
Article (Journal)
Electronic Resource
English
Trajectory , Map , Navigation , Autonomous Robot , Landmarks
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