Learning How Pedestrians Navigate: A Deep Inverse Reinforcement Learning Approach-Reference-Cited by-同舟云学术

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Learning How Pedestrians Navigate: A Deep Inverse Reinforcement Learning Approach

Published:2018-10 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Fahad Muhammad,Chen Zhuo,Guo Yi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8574473/8593358/08593438.pdf?arnumber=8593438

Cited by 29 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. Protecting Vulnerable Road Users: Semantic Video Analysis for Accident Prediction;2023 IEEE Symposium Series on Computational Intelligence (SSCI);2023-12-05

2. SocNavGym: A Reinforcement Learning Gym for Social Navigation;2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN);2023-08-28

3. Inverse Reinforcement Learning of Pedestrian–Robot Coordination;IEEE Robotics and Automation Letters;2023-08

4. An Incremental Inverse Reinforcement Learning Approach for Motion Planning with Separated Path and Velocity Preferences;Robotics;2023-04-20

5. Social aspects of collision avoidance: a detailed analysis of two-person groups and individual pedestrians;Scientific Reports;2023-04-08

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