5 accepted papers
Verification and validation of autonomous driving (AD) systems and components is of increasing importance, as such technology increases in real-world prevalence. Safety-critical scenario generation is a key approach to robustify AD policies through closed-loop training. However, existing approaches …
Verification and validation of autonomous driving (AD) systems and components is of increasing importance, as such technology increases in real-world prevalence. Safety-critical scenario generation is a key approach to robustify AD policies through closed-loop training. However, existing approaches
The fast-growing demand for fully autonomous robots in shared spaces calls for developing trustworthy agents that can safely and seamlessly navigate crowded environments. Recent models for motion prediction show promise in characterizing social interactions in such environments. However, using them
Recent advances in the areas of Multimodal Machine Learning and Artificial Intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision, Natural Language Processing, and Robotics. Whereas many approaches and previous survey pursuits have characterised one…
As robots across domains start collaborating with humans in shared environments, algorithms that enable them to reason over human intent are important to achieve safe inter-play. In our work, we study human intent through the problem of predicting trajectories in dynamic environments. We explore dom…