A critical comparison between Fast and Hector SLAM algorithms
Journal Title: REST Journal on Emerging trends in Modelling and Manufacturing - Year 2017, Vol 3, Issue 2
Abstract
This paper compares between two Simultaneous Localization and Mapping (SLAM) algorithms. SLAM algorithms are used by a mobile robot to build a map for unknown environment and localizing itself in the map related to some landmarks using odometry. In this paper, Robot Operating System (ROS) is used for implementing and simulating Hector SLAM algorithm using a package called Hector mapping and a Fast SLAM algorithm using a package called Gmapping. The criteria for evaluating the performance are time-consumed, the size of the built map, error between the built map and the actual one and the performance variation while the map is increased. Changing the parameters for building the map is also studied, and its influence on the time consumed and the quality of the built map also. Finally, the results of the two algorithms are compared to each other in order to determine which application does Hector SLAM has the upper hand in, and in which applications Fast SLAM is recommended.
Authors and Affiliations
Mustafa Eliwa
Keywords
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- EP ID EP241115
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