Indoor Simultaneous Localization and Mapping (SLAM) Using Laser Range Finder
Simultaneous Localization and Mapping SLAM is one of the most basic necessities for intelligent robots. It enables the robot to fully being autonomous and thus performing many useful tasks. However, most of SLAM implementations require powerful processors to run on, which limits its applications are...
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| Main Author: | |
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| Format: | Final Year Project |
| Language: | English |
| Published: |
IRC
2016
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| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/17192/1/Final%20dissertation.pdf http://utpedia.utp.edu.my/17192/ |
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| Summary: | Simultaneous Localization and Mapping SLAM is one of the most basic necessities for intelligent robots. It enables the robot to fully being autonomous and thus performing many useful tasks. However, most of SLAM implementations require powerful processors to run on, which limits its applications arena. The key purpose behind this project is to technically evaluate the available SLAM algorithms and pick the lightest yet the most accurate one for implementation on low cost Raspberry Pi controlled robotic platform running Robot Operating System ROS.
To fulfil above objectives, the available relevant research efforts towards lightweight SLAM have been thoroughly explored. After that, the most appealing algorithms to the underlined objectives were further studied and technically compared. Eventually, FastSLAM 2.0 was found offering the best potential performance. And so it will be implemented using ROS gmapping package. |
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