Path Following with an Optimal Forward Velocity for a Mobile Robot

In this paper, we present a novel solution for a path following problem in partially-known static environments. Given linearized error dynamic equations, model predictive control (MPC) is employed to produce a sequence of angular velocities. Since the forward velocity of the robot has to be adapted to environmental constraints and robot dynamics while the robot is following a path, we propose an optimal solution to generate the velocity profile. Furthermore, we integrate an obstacle-avoidance behavior using local sensor information with a path-following behavior based on global knowledge. To achieve this, we introduce new waypoints in order to move the robot away from obstacles while the robot still keeps following the desired path. Extensive simulations and experiments with a physical unicycle mobile robot have been conducted to illustrate the effectiveness of our path following control framework.