Multi-modal data fusion has gained popularity due to its diverse applications, leading to an
increased demand for external sensor calibration. Despite several proven calibration …

Automated vehicle technology has recently become reliant on 3D LiDAR sensing for
perception tasks such as mapping, localization and object detection. This has led to a rapid …

Simultaneous Localization and Mapping (SLAM) has been widely applied in various robotic
missions, from rescue operations to autonomous driving. However, the generalization of …

Accurate and reliable sensor calibration is essential to fuse LiDAR and inertial
measurements, which are usually available in robotic applications. In this article, we …

Accurate sensor calibration is a prerequisite for autonomous vehicles' multi-sensor
perception. Even though there are many open-source projects related to sensor calibration …

The technology of autonomous vehicle (AV) is critical in nowadays Intelligent Transportation
Systems. To achieve the fully automated operation for AVs, one important prerequisite is the …

In this paper, we introduce a novel visual-inertial-wheel odometry (VIWO) system for ground
vehicles, which efficiently fuses multi-modal visual, inertial and 2D wheel odometry …

Environmental perception is a crucial component of intelligent driving technology, providing
the informational foundation for intelligent decision-making and collaborative control. Due to …

Accurate and robust calibration is crucial to a multisensor fusion-based system. The
calibration of heterogeneous sensors is particularly challenging because of the huge …

Map-centric SLAM utilizes elasticity as a means of loop closure. This approach reduces the
cost of loop closure while still providing large-scale fusion-based dense maps, when …