Local model predictive control for WMR reactive navigation

This paper presents the use of model predictive control techniques applied to a differential driven WMR for local navigation in dynamic environments. The local trajectory tracking is a relevant idea of this work; hence when dynamic environments or obstacle avoidance policies are considered the navigation path planning should be flexible and constrained to the robot neighborhood. In this sense, a set of dynamic models obtained from the experimental robot system identification are used to predict the horizon of available coordinates. The simulation results are used to orient further experimental results. Moreover, experimental cost function tuning is used to improve the control system performance by testing a set of different trajectories. The benefits of the implementation presented are accuracy, low computational cost, and simplicity.