Hendrik SchoenebergHendrik is a Principal Data Architect at AWS ProServe and helps customers with ADAS/AV platforms, large-scale simulation frameworks and virtual engineering workbenches to achieve their SDV vision. He is passionate about Big Data and Data Analytics and loves his job for its challenges and the opportunity to work with inspiring customers and colleagues.
Streamlining scene detection and visualizing ROS bag files
ADAS/AV feature development is a complex process that starts with ingesting, labeling, and cataloging hundreds of petabytes of data. Searching through the data repository for scenes relevant to specific models being developed and trained is a tedious, time-consuming process. In this session, we’ll introduce how the AWS Autonomous Driving Data Framework (ADDF) helps accelerate the development process. We will show how the scene detection module can be used to run scene analytics for lane detection and topic synchronization, and finally demonstrate how the visualization module can be leveraged to seamlessly stream and visualize stored ROS bag files.