Qiyuan Wu

Semantic and Feature Guided Uncertainty Quantification of Visual Localization for Autonomous Vehicles

The uncertainty quantification of sensor measurements coupled with deep learning networks is crucial for many robotics systems, especially for safety-critical applications such as self-driving cars. This paper develops an uncertainty quantification approach in the context of visual localization for