Yikun Cheng — accepted AI-conference papers

2025

DBaS-Log-MPPI: Efficient and Safe Trajectory Optimization via Barrier States

Fanxin Wang, Haolong Jiang, Chuyuan Tao, Wenbin Wan, Yikun Cheng

IROS 2025

Optimizing trajectory costs for nonlinear control systems remains a significant challenge. Model Predictive Control (MPC), particularly sampling-based approaches such as the Model Predictive Path Integral (MPPI) method, has recently demonstrated considerable success by leveraging parallel computing

Cited by 3 Source ↗Scholar ↗

2022

Improving the Robustness of Reinforcement Learning Policies With ${\mathcal {L}_{1}}$ Adaptive Control

Yikun Cheng, Pan Zhao, Fanxin Wang, Daniel J. Block, Naira Hovakimyan

RA-L 2022

A reinforcement learning (RL) control policy could fail in a new/perturbed environment that is different from the training environment, due to the presence of dynamic variations. For controlling systems with continuous state and action spaces, we propose an add-on approach to robustifying a pre-trai

Cited by 12 Source ↗Scholar ↗