Localization algorithm for autonomous robot

Localization is one of the essential components in the integration of robotics platform before allowing the autonomous robots to be materialised. There are many solutions and techniques to implement localization and solve its problems using the current technology that the world has. One of the solut...

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Bibliographic Details
Main Author: Lim, Jaelynn En Yu
Other Authors: Mo Yilin
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/75545
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Institution: Nanyang Technological University
Language: English
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Summary:Localization is one of the essential components in the integration of robotics platform before allowing the autonomous robots to be materialised. There are many solutions and techniques to implement localization and solve its problems using the current technology that the world has. One of the solutions that is being provided in for navigation in mobile robotics is the implementation of Kalman filters. The Extended Kalman Filter that is implemented for navigation systems in autonomous vehicles will be discussed in this paper. An Extended Kalman Filter algorithm was written in Julia language. A simulation indicating the estimated position and orientation of the autonomous vehicle using the Ubuntu Operating System would be demonstrated. The experimental result of this project illustrates the robust and accuracy of the proposed algorithm for such non-linear systems.