Off-road Autonomous Vehicles Traversability Analysis and Trajectory Planning Based on Deep Inverse Reinforcement Learning-Reference-Cited by-同舟云学术

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Off-road Autonomous Vehicles Traversability Analysis and Trajectory Planning Based on Deep Inverse Reinforcement Learning

Published:2020-10-19 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE Intelligent Vehicles Symposium (IV)
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Author:

Zhu Zeyu,Li Nan,Sun Ruoyu,Xu Donghao,Zhao Huijing

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9304518/9304528/09304721.pdf?arnumber=9304721

Cited by 32 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Traffic navigation via reinforcement learning with episodic-guided prioritized experience replay;Engineering Applications of Artificial Intelligence;2024-11

2. Traversability Analysis and Path Planning for Autonomous Wheeled Vehicles on Rigid Terrains;Drones;2024-08-23

3. Robot-Dependent Traversability Estimation for Outdoor Environments using Deep Multimodal Variational Autoencoders;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. An Overview of Motion-Planning Algorithms for Autonomous Ground Vehicles with Various Applications;SAE International Journal of Vehicle Dynamics, Stability, and NVH;2024-04-03

5. Terrain traversability prediction through self-supervised learning and unsupervised domain adaptation on synthetic data;Autonomous Robots;2024-03-30

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