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Changming Zhang

2 accepted papers

2025

NeuTRL: Neural Trust-Guided Reinforcement Learning for Human-Robot Collaboration

RA-L 2025

Reinforcement Learning from Human Feedback (RLHF) enables robots to learn cooperative strategies aligned with human expectations by incorporating feedback into the learning process. However, existing RLHF methods rely on explicit query-based feedback, which is limited for complex, long-horizon tasks

Cited by 6SourceScholar
2024

Trust Recognition in Human-Robot Cooperation Using EEG

ICRA 2024poster

Collaboration between humans and robots is becoming increasingly crucial in our daily life. In order to accomplish efficient cooperation, trust recognition is vital, empowering robots to predict human behaviors and make trust-aware decisions. Consequently, there is an urgent need for a generalized a…

Cited by 3SourcecodeScholar