With the increasing demand for intelligent services, the sixth-generation (6G) wireless
networks will shift from a traditional architecture that focuses solely on a high transmission …

The collaboration of heterogeneous robots is a hot topic in multi-intelligent agents,
characterized by wide-area coverage and high environmental adaptability. Compared with a …

The autonomy of unmanned aerial vehicles (UAVs)-self-governing in the aerospace
discipline has been a remarkable research area with the development of the advanced …

In this work, we present an end-to-end heterogeneous multi-robot system framework where
ground robots are able to localize, plan, and navigate in a semantic map created in real time …

An automated vehicle operating in an urban environment must be able to perceive and
recognise objects and obstacles in a three-dimensional world for navigation and path …

Generating an accurate and continuous semantic occupancy map is a key component of
autonomous robotics. Most existing continuous semantic occupancy mapping methods …

In the face of large-scale environmental mapping requirements, through the use of
lightweight and inexpensive robot groups to perceive the environment, the multi-robot …

This work addresses the loop closure detection issue by matching the local pose graphs for
semantic visual SLAM. We propose a deep feature matching-based keyframe retrieval …

As an essential procedure of data fusion, LiDAR-camera calibration is critical for
autonomous vehicles and robot navigation. Most calibration methods require laborious …

Place recognition is seen as a crucial factor to correct cumulative errors in Simultaneous
Localization and Mapping (SLAM) applications. Most existing studies focus on visual place …