3 accepted papers
We propose a convex model predictive control (MPC) scheme for a class of affine input systems to reduce the dependence on terminal components and improve real-time control capability. Artificial reference variables are introduced to handle unreachable references, and the terminal set constraint is r
Safe reinforcement learning (RL) aims to learn policy while also ensuring the safety constraints. An increasingly common approach is to design a safety filter based on control barrier function (CBF) or high order control barrier function (HOCBF) for the RL policy. A quadratic programming (QP) is the
This letter proposes an adaptive high-order control barrier function-based iterative linear quadratic regulator (AHOCBF-ILQR) algorithm for real time safety-critical motion planning. Firstly, we propose a HOCBF-ILQR method, where a HOCBF-based controller is designed as a safety filter of ILQR to gua