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

The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …

This article presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry
framework. Building on a highly efficient tightly coupled iterated Kalman filter, FAST-LIO2 …

With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

To model the indeterminacy of human behaviors, stochastic trajectory prediction requires a
sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have …

In this paper, we propose a novel LiDAR-Inertial-Visual sensor fusion framework termed R 3
LIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to …

Learning to predict agent motions with relationship reasoning is important for many
applications. In motion prediction tasks, maintaining motion equivariance under Euclidean …

At the heart of foundation models is the philosophy of" more is different", exemplified by the
astonishing success in computer vision and natural language processing. However, the …

In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …

Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …