This article presents a survey of simultaneous localization and mapping (SLAM) and data
fusion techniques for object detection and environmental scene perception in unmanned …

In recent years, autonomous robots have become ubiquitous in research and daily life.
Among many factors, public datasets play an important role in the progress of this field, as …

Long‐term operation of robots creates new challenges to Simultaneous Localization and
Mapping (SLAM) algorithms. Long‐term SLAM algorithms should adapt to recent changes …

While feature association to a global map has significant benefits, to keep the computations
from growing exponentially, most lidar-based odometry and mapping methods opt to …

Ultra-wideband (UWB) technology is a mature technology that contested other wireless
technologies in the advent of the IoT but did not achieve the same levels of widespread …

Currently, most of the existing fusion methods ignore the rich multi-source information of
different types of sensor nodes in the underwater unknown environment, which makes it …

In this paper, we propose a tightly-coupled, multi-modal simultaneous localization and
mapping (SLAM) framework, integrating an extensive set of sensors: IMU, cameras, multiple …

In multi-robot systems, two important research problems are relative localization between
the robots and global localization of all robots in a common frame. Traditional methods rely …

In this article, we study the problem of estimating the four-degree-of-freedom (3-D position
and heading) robot-to-robot relative frame transformation using onboard odometry and …

In this letter we investigate a tightly coupled Lidar-Inertia Odometry and Mapping (LIOM)
scheme, with the capability to incorporate multiple lidars with complementary field of view …