Obstacle Avoiding Path Following based on Nonlinear Model Predictive Control using Artificial Variables

SANCHEZ, IGNACIO; FERRAMOSCA, ANTONIO; RAFFO, GUILHERME; GONZÁLEZ, ALEJANDRO HERNÁN; DJORGE, AGUSTINA

Conferencia; 19th International Conference on Advanced Robotics; 2019

This work presents a model predictive formulationfor obstacle avoiding path following control for constrainedvehicles. The obstacles are introduced as soft constraints inthe value function, in order to maintain the convexity of stateand output spaces. In this formulation, the path following andobstacle avoidance tasks may introduce local minima solutions-due to their competing costs- known as corner conditions. Inorder to address this problem, a heuristic switch in the form ofadditional decision variables is introduced into the cost function.The proposed solution is based on an extension of ModelPredictive Control (MPC) by using Artificial Variables. Anadditional cost term is included in order to prevent early stopsin the path following task. Simulations results considering anautonomous vehicle subject to input constraints are carried outto illustrate the performance of the proposed control strategy