On-Line path planning for an articulated vehicle based on Model Predictive Control

In this article, a novel on-line path planning algorithm for an articulated vehicle, moving in a partially known and sensory based reconstructed environment, and relying on Model Predictive Control will be presented. The proposed algorithm belongs to the family of bug like path planning algorithms and has the capability to take under consideration the real dynamics of the articulated vehicle. Based on: a) an a priori knowledge of the current and the goal points, and b) a partial sensory based awareness of the surrounding environment, the algorithm is able to tune online the articulated steering angle in order to drive the front and the rear parts of the vehicle from avoiding collision with obstacles, while converging to the goal point. The proposed path planning algorithm is able to produce on-line the next reference way-point, solving the local and sub-optimal problem, while in the sequel a Model Predictive Controller is being utilized for creating the proper control signal, the rate of the articulated angle based on an error dynamics kinematic model of the vehicle. Multiple simulation results are being presented that prove the efficiency of the suggested scheme.