  In this paper, we propose a novel approach to synthesize linear feedback
controllers for navigating in polygonal environments using noisy measurements
and a convex cell decomposition. Our method is based on formulating chance
constraints for the convergence and collision avoidance condition. In
particular, the stability and safety guarantees come from chance Control
Barrier Function (CBF) constraints and chance Control Lyapunov Function (CLF)
constraints, respectively. We use convex over-approximations to get upper
bounds of the constraints, leading to a convex robust quadratic program for
finding the controller. We apply and provide simulation results for equilibrium
control and path control. The result shows that the controller is robust with
the noise input.
