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Wireframe Mapping for Resource-Constrained Robots

In this project, a novel wireframe map structure for resource-constrained robots operating in a rectilinear 2D environment is develop.  The wireframe representation compactly represents geometry as well as occlusions and frontier information.  We formulate a particle filter to suit this wireframe map structure, including a likelihood, merging and updating functions, and resampling functions.  The wireframe together with the particle filter allow for severe discrete map errors to be corrected over time, leading to accurate maps with small storage requirements.  

 

Further description of the algorithms used in this work is provided in the following pdf:

https://msl.stanford.edu/sites/default/files/algos.pdf