Collaborative planning and control of heterogeneous multi-ground unmanned platforms.

With the rapid development of intelligent vehicles, mobile robots, warehousing and logistics, exploration and testing and other industries, multi-platform collaborative work research has become the future research focus of ground platforms. This paper mainly studies the multi-ground platform collaborative system as follows: Combined with the multi-vehicle collaborative scenario, a three-layer system Artificial Intelligence control framework is proposed, which is composed of a task assignment layer, trajectory planning layer and multi-vehicle control layer. Firstly, the multi-car task assignment algorithm based on the Dubins curve is studied. Secondly, the vehicle motion planning algorithm based on the D*Lite algorithm is designed, and the driving direction and the optional grid range are improved. Then, the obstacle scene of multi-vehicle formation is analyzed, two obstacle avoidance schemes of formation are proposed and the process analysis is carried out. Finally, the application in engineering is conducted to verify the effectiveness of obstacle avoidance strategy, trajectory planning strategy and the overall system framework. • A task solving algorithm based on Dubins curve is designed. • An improved D* algorithm is adopted to realize path planning. • A formation algorithm based on model prediction is designed. • Unmanned vehicles are designed and verified by experiment. [ABSTRACT FROM AUTHOR]