Abstract: A takeoff and landing control method of a multimodal air-ground amphibious vehicle includes: receiving dynamic parameters of the multimodal air-ground amphibious vehicle; processing the dynamic parameters by a coupled dynamic model of the multimodal air-ground amphibious vehicle to obtain dynamic control parameters of the multimodal air-ground amphibious vehicle, wherein the coupled dynamic model of the multimodal air-ground amphibious vehicle comprises a motion equation of the multimodal air-ground amphibious vehicle in a touchdown state; and the motion equation of the multimodal air-ground amphibious vehicle in a touchdown state is determined by a two-degree-of-freedom suspension dynamic equation and a six-degree-of-freedom motion equation of the multimodal air-ground amphibious vehicle in the touchdown state; and controlling takeoff and landing of the multimodal air-ground amphibious vehicle according to the dynamic control parameters of the multimodal air-ground amphibious vehicle.

Abstract: A takeoff and landing control method of a multimodal air-ground amphibious vehicle includes: receiving dynamic parameters of the multimodal air-ground amphibious vehicle; processing the dynamic parameters by a coupled dynamic model of the multimodal air-ground amphibious vehicle to obtain dynamic control parameters of the multimodal air-ground amphibious vehicle, wherein the coupled dynamic model of the multimodal air-ground amphibious vehicle comprises a motion equation of the multimodal air-ground amphibious vehicle in a touchdown state; and the motion equation of the multimodal air-ground amphibious vehicle in a touchdown state is determined by a two-degree-of-freedom suspension dynamic equation and a six-degree-of-freedom motion equation of the multimodal air-ground amphibious vehicle in the touchdown state; and controlling takeoff and landing of the multimodal air-ground amphibious vehicle according to the dynamic control parameters of the multimodal air-ground amphibious vehicle.

Abstract: A lane line detection method using a fusion network based on an attention mechanism, and a terminal device are provided. The method includes: synchronously acquiring natural images and point cloud data of a road surface; and inputting the natural images and the point cloud data into a pre-built and trained fusion network to output a lane line detection result. Time series frames and an attention mechanism are added to the fusion network to perform information fusing on the point cloud data and the natural images. Specifically, continuous frames are used to improve detection network performance to deal with complex situations such as label loss and vehicle being blocked; low-dimensional features are stitched with high-dimensional features by Skip Connection to make up for image detail information that is continuously lost as the network goes deeper, and the Decoder module is used to restore image dimensions to obtain a final result.