BreezySLAM: A Simple, efficient, cross-platform Python package for Simultaneous Localization and Mapping (thesis)
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Date
2014Subject
Washington and Lee University -- Honors in Computer Science
Computer algorithms
Application program interfaces (Computer software)
Robotics
Digital mapping -- Computer programs
Robots -- Control systems
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Thesis; [FULL-TEXT FREELY AVAILABLE ONLINE] Suraj Bajracharya is a member of the Class of 2014 of Washington and Lee University. BreezySLAM is a simple, efficient, multiplatform, open--‐source Python library for Simultaneous Localization and Mapping. By using Python C extensions to wrap existing implementations of existing SLAM algorithms, BreezySLAM provides a Python API for SLAM that runs nearly as fast as the original C code. By making a SLAM API available in Python, students and other interested users will be able to get their hands on SLAM very quickly and efficiently. BreezySLAM has been tested with a number of robots in V--‐REP Simulator, as well as on a Neato XV--‐11, with promising results. Suraj Bajracharya