Event-Triggered Maps of Dynamics
Modeling spatial motion patterns in dynamic and non-stationary environments.
This project studies the modeling of spatial motion patterns in non-stationary environments.
The framework combines event-triggered representations with probabilistic and learning-based models to capture changing motion dynamics across space and time.
The work was published at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2025.