2024

Deep Reinforcement Learning for Sim-to-Real Transfer in a Humanoid Robot Barista
Deep Reinforcement Learning for Sim-to-Real Transfer in a Humanoid Robot Barista

Ziyuan Wang, Yefan Lin, Leyu Zhao, Jiahang Zhang, Xiaojun Hei# (# corresponding author)

IEEE International Conference on Robotics and Biomimetics (ROBIO) 2024

In this paper, we study the coffee-making application as an example. We proposed a reinforcement learning robot manipulation method with visual perception for filling-up the sim-to-real gap. We constructed a high-fidelity coffee making digital twin simulation environment.

Deep Reinforcement Learning for Sim-to-Real Transfer in a Humanoid Robot Barista

Ziyuan Wang, Yefan Lin, Leyu Zhao, Jiahang Zhang, Xiaojun Hei# (# corresponding author)

IEEE International Conference on Robotics and Biomimetics (ROBIO) 2024

In this paper, we study the coffee-making application as an example. We proposed a reinforcement learning robot manipulation method with visual perception for filling-up the sim-to-real gap. We constructed a high-fidelity coffee making digital twin simulation environment.

Self-Perceptive Framework: A Manipulation Framework with Visual Compensation for Zero Position Error
Self-Perceptive Framework: A Manipulation Framework with Visual Compensation for Zero Position Error

Ziyuan Wang, Yefan Lin, Jiahang Zhang, Changjiang Han, Xiaojun Hei# (# corresponding author)

IEEE International Conference on Robotics and Automation (ICRA 2025) Under review.

In this paper, to improve the success rate of robot manipulation tasks with zero position problem and reduce the frequency of recalibration, we proposed a robot manipulation framework, the Self-Perceptive Framework(SPF), which uses reinforcement learning and incorporates self-perceptive information.

Self-Perceptive Framework: A Manipulation Framework with Visual Compensation for Zero Position Error

Ziyuan Wang, Yefan Lin, Jiahang Zhang, Changjiang Han, Xiaojun Hei# (# corresponding author)

IEEE International Conference on Robotics and Automation (ICRA 2025) Under review.

In this paper, to improve the success rate of robot manipulation tasks with zero position problem and reduce the frequency of recalibration, we proposed a robot manipulation framework, the Self-Perceptive Framework(SPF), which uses reinforcement learning and incorporates self-perceptive information.

2022

Design a Cloud-enabled Humanoid Robot Application System to Assess the ABA Learning for Autistic Children

Ziyuan Wang, Yiwei Chen, Xiaojun Hei# (# corresponding author)

International Conference on Intelligent Education and Intelligent Research (IEIR) 2022

In this paper we apply the cloud-based robotics and the practical needs of the Applied- Behaviour-Analysis (ABA) learning for autistic children, and design an a cloud-enabled humanoid robot application system, in order to reduce the teacher’s workload.

Design a Cloud-enabled Humanoid Robot Application System to Assess the ABA Learning for Autistic Children

Ziyuan Wang, Yiwei Chen, Xiaojun Hei# (# corresponding author)

International Conference on Intelligent Education and Intelligent Research (IEIR) 2022

In this paper we apply the cloud-based robotics and the practical needs of the Applied- Behaviour-Analysis (ABA) learning for autistic children, and design an a cloud-enabled humanoid robot application system, in order to reduce the teacher’s workload.