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Advanced driver assistance systems (ADAS) and autonomous driving rely on cameras, lidars, radars, and other sensors to accurately perceive their environment. These sensing systems must operate reliably in rain, snow, fog, mud, dust, condensation, and extreme weather conditions.
A dirty camera lens, ice buildup on the lidar, or dirt splatter covering the sensor degrade t...
Advanced driver assistance systems (ADAS) are a key step toward fully autonomous vehicles. Their reliability depends not only on the quality of machine learning models, but also on the system's ability to operate correctly in rare, complex, and unpredictable traffic scenarios. It is such scenarios - the so-called corner cases - that pose the greatest risk to safety, as they o...
Homologation is the process of official vehicle certification for compliance with regulatory requirements, without which no car can receive permission to enter public roads. For autonomous systems and advanced driver assistance systems, this process becomes an extremely complex task, as regulators demand proof of AI safety even in critical situations. Since autonomous driving...
Driver assistance systems (ADAS) depend on accurate sensor calibration to correctly interpret the environment and make safe driving decisions. Cameras, lidar systems, radar, and ultrasonic sensors must be spatially aligned to ensure the sensor fusion channels function.
In real-world vehicle operation, sensor calibration can gradually deteriorate over time due to vibrati...
Modern robotics is rapidly moving towards the creation of systems capable of performing complex manipulation tasks similar to those of the human hand. One of the key challenges in this field is the development and training of multi-fingered robotic hands that can not only grasp objects but also perform precise intra-manipulation actions, such as rotating, pivoting, and re-gra...