This article presents a model predictive control (MPC) coupled with an artificial potential field (APF) to resolve the trajectory tracking while considering the obstacle avoidance. In this article, the obstacle avoidance problem is solved by a local path planning based on the artificial potential field by constructing a virtual goal. A virtual goal is generated to produce an attractive force to guide the mobile robot to a collision-free space. The planned path is controlled by a proportional–integral–derivative (PID) controller to avoid collision. After arriving at the virtual goal, an off-line explicit MPC is calculated to obtain the optimal control inputs to track the reference trajectory. The simulation results show that the proposed method can be applied to control the mobile robot in the environment with one obstacle.

The obstacle avoidance control of mobile robots has been widely investigated for numerous practical applications. In this study, a control scheme is presented to deal with the problem of trajectory tracking while considering obstacle avoidance. The control scheme is simplified into two controllers. First, an existing trajectory tracking controller is used to track. Next, to avoid the possible obstacles in the environment, an obstacle avoidance controller, which is used to determine the fastest collision avoidance direction to follow the boundary of the obstacle at a constant distance, is proposed based on vector relationships between the robot and an obstacle. Two controllers combined via a switch strategy are switched to perform the task of trajectory tracking or obstacle avoidance. The stability of each controller in the control scheme is guaranteed by a Lyapunov function. Finally, several simulations are conducted to evaluate the proposed control scheme. The simulation results indicate that the proposed scheme can be applied to the mobile robot to ensure its safe movement in unknown obstacle environments.

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