Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model-Reference-Cited by-同舟云学术

Software-Defined Active LiDARs for Autonomous Driving: A Parallel Intelligence-Based Adaptive Model

Published:2023-08 Issue:8 Volume:8 Page:4047-4056
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Liu Yuhang¹^ORCID,Sun Boyi²,Tian Yonglin³^ORCID,Wang Xingxia¹^ORCID,Zhu Yin⁴,Huai Rouxing⁵,Shen Yu¹^ORCID

Affiliation:

1. State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

2. Department of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China

3. State Key Laboratory for Management and Control of Complex Systems, and Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China

4. North Automatic Control Technology Institute, Taiyuan, China

5. Beijing Huairou Academy of Parallel Sensing, Beijing, China

Funder

Key Research and Developing Program 2020 of Guangzhou

Key-Area Research and Developing Program of Guangdong Province

Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/7274857/10260249/10163892.pdf?arnumber=10163892

Reference78 articles.

1. RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation

2. An End-to-End Transformer Model for 3D Object Detection

3. SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

4. 3D Object Detection with Pointformer

5. A Survey on Trajectory-Prediction Methods for Autonomous Driving

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