Difference between revisions of "Zenseact Scalable Mapping"

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Latest revision as of 20:30, 10 October 2022

Title Zenseact Scalable Mapping
Summary Scalable mapping through crowd sourcing
Keywords
TimeFrame Fall 2022
References
Prerequisites
Author
Supervisor TBD
Level Master
Status Open


This thesis aims to develop a scalable method to crowdsource certain elements of an HD map by collecting sensor data from a fleet of vehicles and fusing the information into a single coherent road model. The focus is to describe the geometry of lane markers, traffic signs, and natural driving profiles on a large scale, or at least from a handful of drives on the ring roads of Göteborg.

The topic is proposed by Zenseact. More details are available here:

https://career.zenseact.com/jobs/2113621-master-thesis-scalable-mapping-through-crowd-sourcing

About Zenseact: We develop the complete software stack for ADAS and AD, from sensing to actuation. Our focus is to build a single cutting-edge software platform in order to serve various levels of autonomy and offer unequaled scalability at the same time. We operate in Sweden and China.