Building Multi-Layer Data Pipelines for Autonomous Industrial Robots
Session date: Nov 19, 2024 08:00am (Pacific Time)
Discover how modern robotics systems can leverage multi-layered data architectures to serve diverse stakeholder needs, from real-time machine control to business intelligence. Using Urban Machine’s autonomous lumber reclamation robot as a case study, this technical session will demonstrate how to architect a comprehensive data pipeline that processes everything from low-level sensor data to high-level business metrics.
The webinar explores practical implementations of ROS (Robot Operating System) data handling, real-time machine learning inference monitoring, and business KPI tracking through live demonstrations of production systems. We’ll dive into strategies for managing different data velocities—from millisecond-level computer vision metrics to monthly business performance indicators—while maintaining system reliability and data accessibility.
This session covers:
- Architecting multi-stakeholder data pipelines for industrial robotics
- Integrating ROS data streams with business intelligence platforms
- Real-time monitoring of machine learning and computer vision systems
- Building effective dashboards for technical and non-technical stakeholders
- Strategies for cloud replication and data availability
Alex Thiele
Co-Founder & Chief Software Architect, Urban Machine
Alex Thiele is the Co-founder and Chief Software Architect at Urban Machine, where he leads the development of groundbreaking robots that convert construction waste into high-quality reclaimed lumber. Previously a co-founder of Aotu.ai, he developed a smart vision platform capable of scaling to process hundreds of AI video streams, pioneering in the field ahead of the recent AI boom. With a background in robotics and AI, Alex is dedicated to leveraging technology for a greener future.