Gaussian Process Model Predictive Control Based Cooperative Motion Planning Structure for UAGVS

Gaussian process (GP) models based model predictive control (MPC) structure for cooperative motion planning of Unmanned Aerial and Ground Vehicle System (UAGVS) is proposed in this article. The GP models are firstly trained to describe the dynamics of UAVs and UGVs with their uncertainties. Stochastic optimization problems are designed for motion planning and controlling based on the GP models' probabilistic predictions. And for the necessary interactions among agents, the predicted motion information is also communicated with each other, so that they can obtain others' future planned behaviors. Simulation results show that the proposed method exhibit promising effects of motion planning for UAVGS.