Integrated Planning and Control: A Crucial Path Nodes-Based Piecewise Model Predictive Control Strategy

In this letter, an integrated planning and control strategy based on piecewise model predictive control (MPC) is developed to improve the efficiency of planning-control framework. First, a penalty term characterizing the influence of obstacles is merged into the heuristic function of A* algorithm. This enables the planned path to maintain navigability in narrow areas while deviating from obstacles in open areas. Second, to rapidly identify safe regions around the original path, several crucial path nodes (CPNs) are selected, including heading change nodes and constraint change nodes. With the safe regions around these CPNs, a novel method for constructing safe travel corridors (STCs) is developed. Finally, a piecewise MPC is put forward to drive the unmanned ground vehicle (UGV) towards the target node within STCs, which eliminates the requirement for the reference path. This promotes the efficiency of planning-control framework and achieves stronger traveling stability. The proposed strategy is deployed on a UGV platform, and its superiority and effectiveness are demonstrated via real vehicle experiments.