Intelligent Amphibious Ground-Aerial Vehicles: State of the Art Technology for Future Transportation-Reference-Cited by-同舟云学术

Intelligent Amphibious Ground-Aerial Vehicles: State of the Art Technology for Future Transportation

Published:2023-01 Issue:1 Volume:8 Page:970-987
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Zhang Xinyu¹^ORCID,Huang Jiangeng¹^ORCID,Huang Yuanhao²^ORCID,Huang Kangyao³^ORCID,Yang Lei¹^ORCID,Han Yan¹^ORCID,Wang Li¹^ORCID,Liu Huaping³^ORCID,Luo Jianxi⁴^ORCID,Li Jun¹

Affiliation:

1. State Key Laboratory of Automotive Safety and Energy, the School of Vehicle and Mobility, Tsinghua University, Beijing, China

2. School of Vehicle and Mobility, Tsinghua University, Beijing, China

3. Department of Computer Science and Technology, Tsinghua University, Beijing, China

4. Data-Driven Innovation Lab, Singapore University of Technology and Design (SUTD), Singapore

Funder

National High Technology Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/7274857/10024686/09839587.pdf?arnumber=9839587

Reference173 articles.

1. Distributed Multi-Actuator Control for Workload Balancing in Wireless Sensor and Actuator Networks

2. PRIMAL$_2$: Pathfinding Via Reinforcement and Imitation Multi-Agent Learning - Lifelong

3. Airspace Sector Redesign Based on Voronoi Diagrams

4. PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning

5. A Workload Balanced Algorithm for Task Assignment and Path Planning of Inhomogeneous Autonomous Underwater Vehicle System

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