High definition mapping (HDM) is a form of mapping that uses advanced technologies such as LiDAR, satellite imagery, aerial photographs and photogrammetry to create detailed, accurate 3D maps or models of an area. HDM is used for a variety of purposes, from creating virtual tours of a city to helping autonomous vehicles safely navigate roads.

First, I’d like to share a little about myself and the relevant experiences. I worked with high definition mapping.

Most recently I worked on developing a home robot (Astro) at Amazon Lab126, building out the embedded mapping and infrastructure framework.

Prior to that, I worked at AutoX — a self driving vehicle company, mostly a generalist systems engineer. I worked on building and scale out the infrastructure to handle massive amount of data.

In this article, we’ll focus primarily working with point cloud data in terms of infrastructure, compute, data structures, and some algorithms to compute and transform the data.

High Definition Maps

High Definition Maps contains 3D data, produced from include the raw point data (“point cloud”) as well as processed derivatives such as contours and surfaces (DEMs).

HD maps differ from conventional maps in that it is possible to use HD maps for high accuracy and precision localization (e.g. knowing where you are on the road on a centimeter level).

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