The capability of a mobile robot to efficiently and safely perform complex missions is limited
by its knowledge of the environment, namely the situation. Advanced reasoning, decision …

As a fundamental issue in robotics academia and industry, indoor autonomous mobile
robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information …

With the increasing affordability of robot technologies and the reduction in size and weight of
autonomous systems, the deployment of autonomous robotic systems on construction sites …

Simultaneous localization and mapping (SLAM) plays a crucial role in the field of intelligent
mobile robots. However, the traditional Visual SLAM (VSLAM) framework is based on strong …

Mobile robots are widely used in medicine, agriculture, home furnishing, and industry.
Simultaneous localization and mapping (SLAM) is the working basis of mobile robots, so it is …

Traditional simultaneous localization and mapping (SLAM) performs well in a static
environment; however, with the abrupt increase of dynamic points in dynamic environments …

Visual-inertial odometry (VIO) algorithms, fusing various features such as points and lines,
are able to improve their performance in challenging scenes while the running time severely …

Visual–inertial SLAM algorithms empower robots to autonomously explore and navigate
unknown scenes. However, most existing SLAM systems heavily rely on the assumption of …

Fiducial markers can encode rich information about the environment and aid Visual SLAM
(VSLAM) approaches in reconstructing maps with practical semantic information. Current …

3D scene graphs offer a more efficient representation of the environment by hierarchically
organizing diverse semantic entities and the topological relationships among them. Fiducial …