Search Results for author: Dongjie Yu

Found 6 papers, 5 papers with code

BiKC: Keypose-Conditioned Consistency Policy for Bimanual Robotic Manipulation

1 code implementation14 Jun 2024 Dongjie Yu, Hang Xu, Yizhou Chen, Yi Ren, Jia Pan

The predicted keyposes provide guidance for trajectory generation and also mark the completion of one sub-stage task.

Imitation Learning

Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model

1 code implementation19 Jan 2024 Yinan Zheng, Jianxiong Li, Dongjie Yu, Yujie Yang, Shengbo Eben Li, Xianyuan Zhan, Jingjing Liu

Interestingly, we discover that via reachability analysis of safe-control theory, the hard safety constraint can be equivalently translated to identifying the largest feasible region given the offline dataset.

Offline RL reinforcement-learning +1

Reachability Constrained Reinforcement Learning

2 code implementations16 May 2022 Dongjie Yu, Haitong Ma, Shengbo Eben Li, Jianyu Chen

Recent studies incorporate feasible sets into CRL with energy-based methods such as control barrier function (CBF), safety index (SI), and leverage prior conservative estimations of feasible sets, which harms the performance of the learned policy.

reinforcement-learning Reinforcement Learning +2

Rethinking Pretraining as a Bridge from ANNs to SNNs

1 code implementation2 Mar 2022 Yihan Lin, Yifan Hu, Shijie Ma, Guoqi Li, Dongjie Yu

In this work, a new SNN training paradigm is proposed by combining the concepts of the two different training methods with the help of the pretrain technique and BP-based deep SNN training mechanism.

Self-learned Intelligence for Integrated Decision and Control of Automated Vehicles at Signalized Intersections

no code implementations24 Oct 2021 Yangang Ren, Jianhua Jiang, Dongjie Yu, Shengbo Eben Li, Jingliang Duan, Chen Chen, Keqiang Li

This paper develops the dynamic permutation state representation in the framework of integrated decision and control (IDC) to handle signalized intersections with mixed traffic flows.

Autonomous Driving Decision Making

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