3 accepted papers
Lightweight and semantically meaningful environment maps are crucial for many applications in robotics and autonomous driving to facilitate higher-level tasks such as navigation and planning. In this paper we present a novel approach to incrementally build a meaningful and lightweight semantic map d…
Accurate and reliable localization is a fundamental requirement for autonomous vehicles to use map information in higher-level tasks such as navigation or planning. In this paper, we present a novel approach to vehicle localization in dense semantic maps, including vectorized high-definition maps or…
Highly accurate maps of the road infrastructure are a crucial cornerstone for self-driving cars to enable navigation in complex traffic scenarios. Traditional methods for creating detailed maps of road environments involve expensive survey vehicles that cannot keep up with the frequent changes in th…