Storage and Retrieval of Robotic Laser Range Data in Database Systems

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Course project for CSE 544 (grad-level Database Systems). In collaboration with Joshua Fan

As a robot navigates in an indoor environment, it can collect a dataset of local observations using the on-board laser range-finder, which can then be used to train machine learning models for place classification.

The goal of our project is to enable storing images of laser-range observations into a relational database, and retrieving similar images to a query image efficiently. We build a pipeline to extract image features and store them into a relational database following the Bag-of-Visual-Words model, and we implemented FIDS ("Flexible Image Database System") to speed up image retrieval, as well as Locality Sensitive Hashing to store data in a way that allows for faster retrieval. See abstract and report below.

[report] [poster]

Originally posted on 04/01/2018. Last updated on 05/20/2023.


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kaiyutony [at] gmail [dot] com

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