Odometry is crucial for robot navigation, particularly in situations where global positioning
methods like global positioning system are unavailable. The main goal of odometry is to …

Abstract Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. Over the last two decades …

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

We often encounter limited FOV situations due to various factors such as sensor fusion or
sensor mount in real-world robot navigation. However, the limited FOV interrupts the …

Moving object segmentation (MOS) using a 3D light detection and ranging (LiDAR) sensor is
crucial for scene understanding and identification of moving objects. Despite the availability …

The ability to estimate pose and generate maps using 3D LiDAR significantly enhances
robotic system autonomy. However, existing open-source datasets lack representation of …

To ensure the efficiency of robot autonomy under diverse real-world conditions, a high-
quality heterogeneous dataset is essential to benchmark the operating algorithms' …

Connected and Autonomous Vehicles (CAVs) are referred to as self-driving vehicles that will
become an essential component of future intelligent transportation systems. These CAVs will …

The deployment of the robotic system that executes specific task is being challenged by the
prevalence of dynamic objects in real‐world scenes. Two robotic tasks sparked by this …

This paper introduces LAMM, an open-source framework for large-scale multi-session 3D
LiDAR point cloud map merging. LAMM can automatically integrate sub-maps from multiple …