Ensuring safety in human–robot collaboration is one of the main challenges in mobile
robotics today. Semantic maps are a potential solution because they provide semantic …

CLIP is a significant vision-and-language training framework that has shown surprisingly
general understanding of the world, with good performance in many open-ended tasks with …

Accurate obstacle detection plays a crucial role in the creation of high-precision maps within
unstructured terrain environments, as it supplies vital decision-making information for …

Traditional knowledge distillation (KD) relies on a proficient teacher trained on the target
task, which is not always available. In this setting, cross-task distillation can be used …

Monocular depth estimation (MDE) aims to transform an RGB image of a scene into a
pixelwise depth map from the same camera view. It is fundamentally ill-posed due to missing …

It is still challenging to efficiently construct semantic map with a monocular camera. In this
paper, deep learning is introduced to combined with SLAM to realize semantic map …

Three-dimensional (3D) spatial data, terrain type, and physical properties of field terrain are
very important information for mobile robots in trajectory planning, force adjustment, motion …

We make full use of the pre-known knowledge of environment, and establish a hierarchical
semantic map offline for large-scale outdoor environment. The map contains semantic …