Visually-guided motion planning for autonomous driving from interactive demonstrations

The successful integration of autonomous robots in real-world environments strongly depends on their ability to reason from context and take socially acceptable actions. Current autonomous navigation systems mainly rely on geometric information and hard-coded rules to induce safe and socially compliant behaviors. Yet, in unstructured urban...

Low-level radar data based road user detection

In order to achieve redundancy and improve the robustness of an autonomous driving system, radar is a suitable choice for road user detection task in severe working conditions (e.g. darkness, bad weather). However, the real-time multi-class radar based road user detection algorithm is less explored compared with camera and LiDAR solutions. To...

Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map

To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving scene. Motion prediction can be done based on experience and recently observed series of past events, and entails reasoning about probable outcomes with these past ob- servations. Aspects that...