Recently, with the in-depth development of Industry 4.0 worldwide, mobile robots have
become a research hotspot. Indoor localization has become a key component in many fields …

When multiple robots are involved in the process of simultaneous localization and mapping
(SLAM), a global map should be constructed by merging the local maps built by individual …

As a key method of ocean exploration, the positioning accuracy of autonomous underwater
vehicles (AUVs) directly influences the success of subsequent missions. This study aims to …

One of the most frequently used approaches to represent collaborative mapping are
probabilistic occupancy grid maps. These maps can be exchanged and integrated among …

Purpose Indoor localization is a key tool for robot navigation in indoor environments.
Traditionally, robot navigation depends on one sensor to perform autonomous localization …

There is a problem in that the existing visual simultaneous localization and mapping (SLAM)
algorithm mainly applied to static scenes is less likely to be applied to dynamic scenes …

Simultaneous localization and mapping (SLAM) is the basis for many robotic applications.
Most SLAM algorithms are based on the assumption that the scene is static. In real-world …

Purpose This study aims to present an automated guided logistics robot mainly designed for
pallet transportation. Logistics robot is compactly designed. It could pick up the pallet …

Purpose This paper aims to present a multi-source information fusion algorithm based on
factor graph for autonomous underwater vehicles (AUVs) navigation and positioning to …

Simultaneous localization and mapping (SLAM) is the key technology in the implementation
of robot intelligence. Compared with the camera, the higher accuracy and stability can be …