Melvinton, Jerryko and Rusyadi, Rusman and Galinium, Maulahikmah (2022) Development of Vision Based Indoor Navigation for Autonomous Mobile Robot Utilizing RTAВ-Мар. Bachelor thesis, Swiss German University.
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Abstract
The use of autonomous mobile robots (AMR), which can carry out a variety of activities including distribution, inventory management, and monitoring, is common in interior settings. Simultaneous Localization and Mapping (SLAM) and visual odometry allow AMRs to navigate independently and precisely, which is necessary for them to operate in these situations. By examining the changes in visual data collected from one or two cameras affixed to the robot, the technique known as "visual odometry" calculates the motion of the robot. Slam is a method that uses sensor data or an image to create a map of the robot's surroundings while concurrently estimating the robot's attitude. Real- Time Appearance-Based Mapping is a well-liked SLAM framework that is frequently utilized in indoor robot navigation. A graph-based SLAM system called RTAB-Map makes use of visual characteristics to map the surrounding area and infer the robot's posture. It can manage dynamic environments, where the environment's appearance varies over time, and it can also bounce back from tracking errors.
Item Type: | Thesis (Bachelor) |
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Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T59.5 Automation |
Divisions: | Faculty of Engineering and Information Technology > Department of Mechatronics Engineering |
Depositing User: | Mr Arinton Sinaga |
Date Deposited: | 11 Dec 2024 07:11 |
Last Modified: | 11 Dec 2024 07:11 |
URI: | http://repository.sgu.ac.id/id/eprint/2714 |
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