4 papers
NeMo-map: Neural Implicit Flow Fields for Spatio-Temporal Motion Mapping
Yufei Zhu, Shih-Min Yang, Andrey Rudenko +3
Safe and efficient robot operation in complex human environments can benefit from good models of site-specific motion patterns. Maps of Dynamics (MoDs) provide such models by encod…
Trajectory prediction for heterogeneous agents: A performance analysis on small and imbalanced datasets
Tiago Rodrigues de Almeida, Yufei Zhu, Andrey Rudenko +4
Robots and other intelligent systems navigating in complex dynamic environments should predict future actions and intentions of surrounding agents to reach their goals efficiently…
Long-Term Human Motion Prediction Using Spatio-Temporal Maps of Dynamics
Yufei Zhu, Andrey Rudenko, Tomasz P. Kucner +2
Long-term human motion prediction (LHMP) is important for the safe and efficient operation of autonomous robots and vehicles in environments shared with humans. Accurate prediction…
Discrete Contrastive Learning for Diffusion Policies in Autonomous Driving
Kalle Kujanpää, Daulet Baimukashev, Farzeen Munir +4
Learning to perform accurate and rich simulations of human driving behaviors from data for autonomous vehicle testing remains challenging due to human driving styles' high diversit…