In this article a switching model predictive control scheme for an articulated vehicle under varying slip angles is being presented. For the non-holonomic articulated vehicle, the non-linear kinematic model that is able to take under consideration the effect of the slip angles is extracted. This model is transformed into an error dynamics model, which in the sequence is linearized around multiple nominal slip angle cases. The existence of the slip angles has a significant effect on the vehicle's path tracking capability and can significantly deteriorate the performance of the overall control scheme. Based on the derived multiple error dynamic models, the varying slip angle is being considered as the switching rule and a corresponding switching mode predictive control scheme is being designed that it is also able to take under consideration: a) the constrains on the control signals and b) the state constraints. Multiple simulation results are being presented that prove the efficacy of the overall suggested scheme.

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.

This article satisfies obstacle avoidance based on modified path-planning for an articulated robot under limited knowledge environment. The knowledge from the environment can be obtained using local range sensors mounted on the robot. The modification of the A-star algorithm is presented as the basis approach for a new smooth path-planning. A three-circle zone concept is proposed to generate a free collision path with minimum length. The corresponding kinematic model is being specified to produce lateral and longitudinal as a control signals under the limitations of the robot dynamic constraints. The kinematic model of the articulated robot is calculated and derived to use it in the motion planning. Motion behavior between the initial and the destination points under unavailable map of environment with low computation cost are presented. A method for nonholonomic smooth motion planning for articulated robot is established by using MATLAB. Simulate results showed the smoothness and shortest way to drive the robot over such path.