Adaptive step rotation in biped walking

We want to enable the robot to reorient its feet in order to face its direction of motion. Model Predictive Control schemes for biped walking usually assume fixed feet rotation since adapting them online leads to a nonlinear problem. Nonlinear solvers do not guarantee the satisfaction of nonlinear constraints at every iterate and this can be problematic for the real-time operation of robots. We propose to define safe linear constraints that are always inside the intersection of the nonlinear constraints. We make simulations of the robot walking on a crowd and compare the performance of the proposed method with respect to the original nonlinear problem solved as a Sequential Quadratic Program.