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Tongqing Chen

4 accepted papers

2023

Inverse Perspective Mapping-Based Neural Occupancy Grid Map for Visual Parking

ICRA 2023poster

Sensing environmental obstacles and establishing an occupancy map of surroundings are critical to achieving automated parking for autonomous vehicles. This paper presents a method to obtain surrounding occupancy information from inverse perspective mapping (IPM) images. This method uses the easily-a…

Cited by 6SourceScholar
2023

Traffic Flow-Based Crowdsourced Mapping in Complex Urban Scenario

RA-L 2023

An accurate road topological structure is of great importance for autonomous driving in complex urban environments. Currently, most autonomous vehicles highly rely on the High-Definition map (HD map) to cruise across the city. Without the prior map, it's hard for vehicles to find right-turning and l

Cited by 13SourceScholar
2021

A Light-Weight Semantic Map for Visual Localization towards Autonomous Driving

ICRA 2021poster

Accurate localization is of crucial importance for autonomous driving tasks. Nowadays, we have seen a lot of sensor-rich vehicles (e.g. Robo-taxi) driving on the street autonomously, which rely on high-accurate sensors (e.g. Lidar and RTK GPS) and high-resolution map. However, low-cost production ca…

Cited by 128SourceScholar
2020

AVP-SLAM: Semantic Visual Mapping and Localization for Autonomous Vehicles in the Parking Lot

IROS 2020poster

Autonomous valet parking is a specific application for autonomous vehicles. In this task, vehicles need to navigate in narrow, crowded and GPS-denied parking lots. Accurate localization ability is of great importance. Traditional visual-based methods suffer from tracking lost due to texture-less reg…

Cited by 162SourceScholar