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Hi, I am Yuan Shijie. Nice to meet you! 👋

😊 About me

  • 📫 Email: [email protected]
  • 🎓 Master student in Hunan University, Changsha, China. Received the B.E. degree from Dalian University of Technology, in 2021.
  • 🔥 Research interests: Motion Planning, Safe Reinforcement Learning, Decision Making for Autonomous Driving 🚗

Jay's Projects

automatedvaletparking icon automatedvaletparking

We use hybrid a star and optimization-based method for trajectory planning of the autonomous vehicle parking

cleanrl icon cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

d3rlpy icon d3rlpy

An offline deep reinforcement learning library

dig-into-apollo icon dig-into-apollo

Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.

elegantrl icon elegantrl

Cloud-native Deep Reinforcement Learning. 🔥

gpir icon gpir

[ICRA'22] Real-Time Trajectory Planning for Autonomous Driving with Gaussian Process and Incremental Refinement

highway-env icon highway-env

A minimalist environment for decision-making in autonomous driving

on_ramp_merge_safe_rl icon on_ramp_merge_safe_rl

we combine safe reinforcement learning with MPC to enhance the safety in the on-ramp merging scenario

paperreading icon paperreading

PaperReading Notes concerning Motion Planing & Reinforcement Learning & Robotics & Autonomous Driving

phd-bibliography icon phd-bibliography

References on Optimal Control, Reinforcement Learning and Motion Planning

rarnop19 icon rarnop19

MIT 16.S498: Risk Aware and Robust Nonlinear Planning (rarnop) by Ashkan Jasour

rtd_tutorial icon rtd_tutorial

Get started with Reachability-based Trajectory Design for static obstacles

stable-baselines3 icon stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

tianshou icon tianshou

An elegant PyTorch deep reinforcement learning library.

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