3 papers
eess.SY2026
Probabilistic Recursively Feasible Motion Planning Under Uncertain Environments
Hyeontae Sung, Hyeongchan Ham, Junyoung Park +2
Safe motion planning in uncertain, time-varying environments is challenging because the safe region can change unpredictably across planning steps, often causing a loss of recursiv…
eess.SY2026
Sampling-Based Safety Filter with Probabilistic Restrictiveness Guarantee
Junyoung Park, Hyeontae Sung, Heejin Ahn
Ensuring safety is a critical requirement for autonomous systems, yet providing formal guarantees for nominal controllers remains a significant challenge. In this paper, we propose…
eess.SY2025
Recursively Feasible Chance-constrained Model Predictive Control under Gaussian Mixture Model Uncertainty
Kai Ren, Colin Chen, Hyeontae Sung +3
We present a chance-constrained model predictive control (MPC) framework under Gaussian mixture model (GMM) uncertainty. Specifically, we consider the uncertainty that arises from…