A new predictive motion control of a planar vehicle under uncertainty via convex optimization

Abstract

This paper proposes an optimization-based planning framework for target tracking of a planar vehicle in the presence of some moving obstacles and uncertainty resources. The framework is modeled based on Linear-Time Varying Model Predictive Control (LTV-MPC). Moreover, a successive linearization approach is presented to formulate the obstacle avoidance mission as a set of linear constraints. Finally this LTV-MPC problem is translated to a close-form convex optimization problem by applying some mathematical and algebraic simplifications. Simulation results show beneficially of the proposed path planning method to navigate an autonomous vehicle successfully regardless of different uncertainty resources.