This letter presents a real-time 3D LiDAR map** framework based on global matching
cost minimization. The proposed method constructs a factor graph that directly minimizes …

This article presents GLIM, a 3D range-inertial localization and map** framework with
GPU-accelerated scan matching factors. The odometry estimation module of GLIM employs …

LiDAR-based localization and map** is one of the core components in many modern
robotic systems due to the direct integration of range and geometry, allowing for precise …

In mobile robotics, scan matching of point clouds using Iterative Closest Point (ICP) allows
estimating sensor displacements. It may prove important to assess the associated …

The fusion of Iterative Closest Point (ICP) registrations in existing state estimation
frameworks relies on an accurate estimation of their uncertainty. In this paper, we study the …

Quantification of uncertainty in point cloud matching is critical in many tasks such as pose
estimation, sensor fusion, and gras**. Iterative closest point (ICP) is a commonly used …

The Exobiology Extant Life Surveyor (EELS) is a snake-like mobile instruments platform
under development at Jet Propulsion Laboratory (JPL) for a mission concept to find …

Exploration of a complex underwater environment without an a priori map is beyond the
state of the art for autonomous underwater vehicles (AUVs). Despite several efforts …

Recently, there has been an arms race of pose forecasting methods aimed at solving the
spatio-temporal task of predicting a sequence of future 3D poses of a person given a …

Accurate and robust localization is essential for autonomous mobile robots. Map matching
based on Light Detection and Ranging (LiDAR) sensors has been widely adopted to …