AIS Lab is pleased to host a seminar with Dr. Sukkeun Kim, Researcher at Karlsruhe Institute of Technology (KIT). Researchers and students interested in related fields are warmly invited to attend.

Speaker: Dr. Sukkeun Kim (Karlsruhe Institute of Technology, KIT)
Title: Particle Flow-based Filters and Deterministic Prior Sample Set Prediction
Date: Wednesday, August 19, 2026, 6:00 PM
Venue: Munji L401 (In-person seminar only)

Particle flow-based filters migrate samples toward the posterior distribution instead of relying on importance weighting, providing an effective approach to mitigating the particle degeneracy problem in particle filters.

This seminar introduces various particle flow-based filtering methods and provides numerical examples to explain their fundamental concepts and applications. In addition, several approaches for generating deterministic prior sample sets in the prediction step of particle flow-based filters will be presented and discussed.

The seminar will conclude with evaluation results in a radar target tracking scenario involving discontinuities, demonstrating significant improvements compared with the Extended Kalman Filter and conventional particle filtering methods.