Local Path Planning Method for Unmanned Vehicle Based on Model Predictive Control in Hospital Environment

In order to address the obstacle avoidance problem of driverless vehicles in hospital environment, a local path planning method based on model predictive control is proposed. Firstly, the potential field model of driving environment factors including obstacles, environmental vehicles, roads, and target points is established by using artificial potential field theory. Then, based on model predictive control algorithm combined with driving environment potential field, trajectory planning and tracking are transformed into a unified constrained optimization problem. The objective function and constraint conditions of local path planning for unmanned vehicles are designed, and roll is introduced to the dynamic optimization mechanism. The simulation results show that the error between the path planning and the expected path is less than 0.1 m, the time consumption is at least 3.3 s, and it has strong robustness, which can effectively solve the obstacle avoidance problem of local path of unmanned vehicles.