Safe Control Synthesis With Uncertain Dynamics and Constraints

This paper considers safe control synthesis for dynamical systems with either probabilistic or worst-case uncertainty in both the dynamics model and safety constraints. We formulate novel robust (worst-case) Lyapunov function (CLF) barrier (CBF) constraints that take into account effect of case. show formulation leads to a second-order cone program (SOCP), which enables efficient stable synthesis. evaluate our approach PyBullet simulations an autonomous robot navigating unknown environments compare performance baseline CLF-CBF quadratic programming approach.