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In this video, Clemens, our CTO, introduces the Persival Sensor Performance Test Bench. It measures the actual performance of lidar and radar sensors across different targets, materials, distances, and viewing angles. With these measurements, you can assess sensor capabilities beyond the data sheet, compare sensor configurations, and validate your sensor models. Tutorial 15: How to measure the performance of perception sensors Topics Covered Sensor Performance Measurement: Le

Reliable perception is one of the fundamental requirements for automated driving systems on-road and especially off-road. While lidar, radar, and camera sensors perform remarkably well under clear weather conditions, their behavior can change significantly when visibility deteriorates.

When we talk about lidar simulation, most discussions focus on sensor models, ray tracing, or point cloud generation. But in many real-world applications, the biggest challenge lies elsewhere: the materials.

Simulating lidar sounds straightforward at first: send out light, measure the distance, and construct the point cloud. In practice, however, the challenge lies in what happens in between. The way infrared light interacts with the world is anything but simple, and without modeling that interaction correctly, even the best sensor model will fall short.

The DIN SAE SPEC 91471 offers a structured way to assess lidar performance. In this blog post, we will explore key performance tests, each critical for understanding lidar capabilities.

In this video, Clemens, our CTO, introduces the Persival Weather Test Bench. It automatically records sensor measurements in adverse weather conditions, such as rain, snow, and fog. With these measurements, you can evaluate how perception sensors like lidar, radar, and cameras perform under real-world weather conditions. Tutorial 14: How to measure weather influence on perception sensors Topics Covered Weather Impact on Perception Sensors: Learn how environmental conditions a