The ability of intelligent unmanned platforms to achieve autonomous navigation and
positioning in a large-scale environment has become increasingly demanding, in which …

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 …

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 …

Mobile robots should be aware of their situation, comprising the deep understanding of their
surrounding environment along with the estimation of its own state, to successfully make …

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 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 …

Visual and lidar Simultaneous Localization and Mapping (SLAM) algorithms benefit from the
Inertial Measurement Unit (IMU) modality. The high-rate inertial data complement the other …

Sensor calibration is a fundamental step for improving the performance in sensor fusion, the
aim of which is to spatially and temporally register sensors with respect to each other. This …

Accurate position is important for intelligent vehicles especially in unknown environments
without prior information. Light Detection and Ranging (LiDAR) has shown great potential in …

Recent years have witnessed a remarkable growth of micro aerial vehicle (MAV)
technologies, which are desirable for many applications, eg, warehouse inventory …