The common SLAM algorithm is based on the visual spatial relationship theory established
with the static environment as the basic assumption. The static assumption of the scene is …

Robust egomotion estimation is a key prerequisite for making a robot truly autonomous. In
previous work, a multimodel extension of random sample consensus (RANSAC) was …

Robust ego-motion estimation in urban environments is a key prerequisite for making a
robot truly autonomous, but is not easily achievable as there are two motions involved: the …

In this contribution, we propose to improve the grid map occupancy estimation method
developed so far based on belief function modeling and the classical Dempster's rule of …

Localization and pose estimation algorithms play an important role in intelligent
transportation systems (ITSs), as ITS need to accurately sense and understand the traffic …

基于激光点云地图的动态障碍剔除是同步定位与建图(simultaneous localization and mapping,
SLAM) 研究领域的难题之一. 动态障碍的移动轨迹不仅会遮挡真实的静态环境信息 …

High‐flying unmanned aerial vehicles (UAVs) are transforming industrial and research
agriculture by delivering high spatiotemporal resolution data on a field environment. While …

To reduce the data size of metric map and map matching computational cost in unmanned
ground vehicle self-driving navigation in urban scenarios, a metric-topological hybrid map …

An occupancy grid map is a common world representation for mobile robotics navigation.
Usually, the information stored in every cell is the probability on the occupancy state. In this …

In this paper, we present a robust RBPF-SLAM algorithm for mobile robots in non-static
environments. We propose an approach for sampling particles from multiple ancestor sets …