Path-following control of autonomous ground vehicles based on input convex neural networks

This paper studies the path-following problems in autonomous ground vehicles (AGVs) through predictive control and neural network modeling. Considering the model of AGVs is usually difficult to construct by first principles accurately, a data-driven approach based on deep neural networks is proposed to deal with the system identification tasks. Although deep neural networks have good representation capability for complex system, they are still …