The dynamic mechanical wheel-ground interaction is extremely complex when off-road vehicles are driven on soft soil pavements， and the extent of wheel sagging and traversability are of significant interest in the field of vehicle

To solve the location and path planning challenges for intelligent vehicles in GPS-restricted underground parking lots， we employ a vision-based approach that combines binocular offline mapping and monocular online localization to

With the development of equipment intelligence， vehicle path planning in complex off-road environments has become a key technology， which is integral to the development of military forces and the intelligence of military equipment

With the continuous development of military intelligence， equipment path optimization in off-road environments has become one of the most important research fields in recent years and plays an important role in promoting the devel

To achieve accurate and rapid interpretation of in-situ soil mechanical parameters and quantitatively evaluate military equipment mobility， an inversion method for soil Mohr-Coulomb parameters is established based on the dynamic c

The geomorphological characterization of Mars is complex. Therefore， to ensure the safe driving of rover， it is essential to understand the surface state around the rover through images captured by on-board digital cameras. The im

Soil in-situ penetration technology is an important method for obtaining its physical and mechanical parameters with the advantages of accuracy， rapidity， and continuity. It has a wide range of applications in marine geotechnical

This paper proposes a feature-matching algorithm based on an adaptive search radius to improve the accuracy of SLAM localization and mapping. This method can overcome the problem in which the search radius of feature matching is f

ICESat-2 is the world's first laser altimetry satellite to use photon counting technology. It provides high-precision， three-dimensional， large-scale ground data that can be obtained rapidly. Altimetry data obtained using photon d

Existing deep learning-based terrain classification methods are mainly for remote sensing imagery； however， the spatial information of point clouds is underutilized. Specifically， the fusion of heterologous features is insufficien

The unsupervised representation learning of point clouds is crucial for understanding and analyzing point clouds， and a 3D reconstruction-based autoencoder is an important architecture in unsupervised learning. To address the rota

The inference of complete three-dimensional （3D） shape and semantic scene information from partial observations is crucial for various applications， such as autonomous driving， robotic vision， and metaverse ecosystem construction.

The development of an emergency return vehicle for lunar exploration is crucial for future manned Chinese lunar exploration missions. To meet the needs of emergency life insurance and short distance movement on the moon surface， t

Vehicles with varying loads deform soft-soil grounds， and the depth of their wheel intrusion is a crucial parameter for evaluating vehicle trafficability on soft soil. This study introduces a novel method that combines the Continu

To solve the trafficability problem of track equipment on super-wetting clay soil， this study investigates the evaluation indexes of track equipment trafficability on super-wetting clay soil， and suggests revised trafficability ru

The surface of Mars is a complex terrain covered with soft soil， which poses significant risks of subsidence， high slip， or even collapse for rovers exploring the planet. A thorough analysis of rover trafficability and effective p