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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sg-ntu-dr.10356-755452023-07-07T17:16:12Z Localization algorithm for autonomous robot Lim, Jaelynn En Yu Mo Yilin School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 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. Bachelor of Engineering 2018-06-01T07:27:57Z 2018-06-01T07:27:57Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75545 en Nanyang Technological University 58 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Lim, Jaelynn En Yu Localization algorithm for autonomous robot |
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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. |
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Mo Yilin |
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Mo Yilin Lim, Jaelynn En Yu |
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Final Year Project |
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Lim, Jaelynn En Yu |
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Lim, Jaelynn En Yu |
title |
Localization algorithm for autonomous robot |
title_short |
Localization algorithm for autonomous robot |
title_full |
Localization algorithm for autonomous robot |
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Localization algorithm for autonomous robot |
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Localization algorithm for autonomous robot |
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localization algorithm for autonomous robot |
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2018 |
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http://hdl.handle.net/10356/75545 |
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1772827377428070400 |