Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios-Reference-Cited by-同舟云学术

Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios

Published:2023-10-01 Issue: Volume: Page:
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Container-title:2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Lu Yiren¹,Fu Justin¹,Tucker George²,Pan Xinlei¹,Bronstein Eli¹,Roelofs Rebecca¹,Sapp Benjamin¹,White Brandyn¹,Faust Aleksandra²,Whiteson Shimon¹,Anguelov Dragomir¹,Levine Sergey²

Affiliation:

1. Waymo Research

2. Google Research, Brain Team

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10341341/10341342/10342038.pdf?arnumber=10342038

Reference54 articles.

1. Alvinn: An autonomous land vehicle in a neural network;Pomerleau;Advances in neural information processing systems,1988

2. End to end learning for self-driving cars;Bojarski;arXiv preprint,2016

3. End-to-End Driving Via Conditional Imitation Learning

4. Long-Tail Prediction Uncertainty Aware Trajectory Planning for Self-driving Vehicles

5. A reduction of imitation learning and structured prediction to no-regret online learning;Ross,2011

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