Nonlinear model predictive control for wheeled mobile robot in dynamic environment

This paper address the set-point regulation problem of a nonholonomic wheeled mobile robot with obstacle avoidance in a known dynamic environment populated with static and moving obstacles subject to robot kinematic and dynamic constraints by using the nonlinear model predictive control in polar coordinate. The terminal state penalty, terminal state constraints, and the input saturation constraints are taken into consideration in this optimization problem to guarantee the closed-loop regulation performance and stability. Simulation results are shown for illustrating the effectiveness of the control algorithm in steering a nonholonomic wheeled mobile robot.