A Graph-based Approach to Solving SLAM: Simultaneous Localization and Mapping
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2016
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Swarthmore College. Dept. of Engineering
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Thesis (B.A.)
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en_US
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Full copyright to this work is retained by the student author. It may only be used for non-commercial, research, and educational purposes. All other uses are restricted.
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Abstract
The ability to map a previously unseen environment is often considered a prerequisite for any truly autonomous robot. Since sensors and motors are often imprecise, it is necessary to find a way to identify and correct error as it accumulates. This problem is often referred to as simultaneous localization and mapping (SLAM), and it has been an active area of research in the field of robotics for the last 20 years. The goal of this project was to implement GraphSLAM [7], a solution to the SLAM problem. This algorithm adjusts the robot positions and the map in order to minimize disagreement between measurements. Ultimately, the algorithm was successfully implemented; however, a small issue with the camera offset still needs to be corrected before the algorithm can be applied to real-world scenarios.