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As the world of automotive technology progresses toward a future of partially and highly automated vehicles, ensuring the utmost safety in these advanced systems becomes paramount. A key factor in achieving this level of safety is the accurate calibration of the sensor suites that power these vehicles‘ perception capabilities. Introduction: The Need for Robust Perception In modern vehicles with many sensors such as cameras, lidars, and radars, redundancy is the foundation f

1) What is your academic career like? What did you do before Spleenlab? My academic career includes a Master’s degree in Engineering Computer Science from TU Ilmenau with specialization in Cognitive Systems and Robotics. Before joining Spleenlab, I worked at Easterngraphics where I was involved in image classification, search engine development, backend and frontend development, and synthetic data generation.

How can fully automated locomotion be enabled in a cost-effective and safe manner while minimizing the use for sensor technology and the effort for data labeling? A new and groundbreaking approach is monocular depth estimation, which in combination with a deep learning approach can enable exactly this.