no code implementations • 28 Nov 2022 • Yuanyuan Shi, Zongyi Li, Huan Yu, Drew Steeves, Anima Anandkumar, Miroslav Krstic
State estimation is important for a variety of tasks, from forecasting to substituting for unmeasured states in feedback controllers.
no code implementations • 13 Apr 2022 • Sven Brüggemann, Drew Steeves, Miroslav Krstic
In this work, we combine {Model Predictive Control} (MPC) and Control Barrier Function (CBF) design {methods} to create a hierarchical control law for simultaneous lane-keeping (LK) and obstacle avoidance (OA): at the low level, MPC performs LK via trajectory tracking during nominal operation; and at the high level, different CBF-based safety filters that ensure both LK and OA are designed and compared across some practical scenarios.