10 citations · 21 across the 8 of their papers we have counts for
8 papers
Autonomous Flights inside Narrow Tunnels
Luqi Wang, Yan Ning, Hongming Chen +5
Multirotors are usually desired to enter confined narrow tunnels that are barely accessible to humans in various applications including inspection, search and rescue, and so on. Th…
SEPT: Standard-Definition Map Enhanced Scene Perception and Topology Reasoning for Autonomous Driving
Muleilan Pei, Jiayao Shan, Peiliang Li +4
Online scene perception and topology reasoning are critical for autonomous vehicles to understand their driving environments, particularly for mapless driving systems that endeavor…
How to predict on-road air pollution based on street view images and machine learning: a quantitative analysis of the optimal strategy
Hui Zhong, Di Chen, Pengqin Wang +4
On-road air pollution exhibits substantial variability over short distances due to emission sources, dilution, and physicochemical processes. Integrating mobile monitoring data wit…
WING: Wheel-Inertial Neural Odometry with Ground Manifold Constraints
Chenxing Jiang, Kunyi Zhang, Sheng Yang +3
In this paper, we propose an interoceptive-only odometry system for ground robots with neural network processing and soft constraints based on the assumption of a globally continuo…
MetaFollower: Adaptable Personalized Autonomous Car Following
Xianda Chen, Kehua Chen, Meixin Zhu +5
Car-following (CF) modeling, a fundamental component in microscopic traffic simulation, has attracted increasing interest of researchers in the past decades. In this study, we prop…
SIMPL: A Simple and Efficient Multi-agent Motion Prediction Baseline for Autonomous Driving
Lu Zhang, Peiliang Li, Sikang Liu +1
This paper presents a Simple and effIcient Motion Prediction baseLine (SIMPL) for autonomous vehicles. Unlike conventional agent-centric methods with high accuracy but repetitive c…
FM-Fusion: Instance-aware Semantic Mapping Boosted by Vision-Language Foundation Models
Chuhao Liu, Ke Wang, Jieqi Shi +2
Semantic mapping based on the supervised object detectors is sensitive to image distribution. In real-world environments, the object detection and segmentation performance can lead…
BEVGPT: Generative Pre-trained Large Model for Autonomous Driving Prediction, Decision-Making, and Planning
Pengqin Wang, Meixin Zhu, Hongliang Lu +5
Prediction, decision-making, and motion planning are essential for autonomous driving. In most contemporary works, they are considered as individual modules or combined into a mult…