most citedMeta Preference Learning for Fast User Adaptation in Human-Supervisory Multi-Robot Deployments

2 citations · 3 across the 2 of their papers we have counts for

collaborators

6 papers

cs.RO2021

Synthesized Trust Learning from Limited Human Feedback for Human-Load-Reduced Multi-Robot Deployments

Yijiang Pang, Chao Huang, Rui Liu

Human multi-robot system (MRS) collaboration is demonstrating potentials in wide application scenarios due to the integration of human cognitive skills and a robot team's powerful…

cs.RO20212 cited

Meta Preference Learning for Fast User Adaptation in Human-Supervisory Multi-Robot Deployments

Chao Huang, Wenhao Luo, Rui Liu

As multi-robot systems (MRS) are widely used in various tasks such as natural disaster response and social security, people enthusiastically expect an MRS to be ubiquitous that a g…

cs.RO2021

Repairing Human Trust by Promptly Correcting Robot Mistakes with An Attention Transfer Model

Ruijiao Luo, Chao Huang, Yuntao Peng +2

In human-robot collaboration (HRC), human trust in the robot is the human expectation that a robot executes tasks with desired performance. A higher-level trust increases the willi…

cs.RO2020

Robot Inner Attention Modeling for Task-Adaptive Teaming of Heterogeneous Multi Robots

Chao Huang, Rui Liu

Attracted by team scale and function diversity, a heterogeneous multi-robot system (HMRS), where multiple robots with different functions and numbers are coordinated to perform tas…

eess.SY20201 cited

Cross-Layer Design of Automotive Systems

Zhilu Wang, Hengyi Liang, Chao Huang +1

With growing system complexity and closer cyber-physical interaction, there are increasingly stronger dependencies between different function and architecture layers in automotive…

cs.RO2020

Inner Attention Supported Adaptive Cooperation for Heterogeneous Multi Robots Teaming based on Multi-agent Reinforcement Learning

Chao Huang, Rui Liu

Humans can selectively focus on different information based on different tasks requirements, other people's abilities and availability. Therefore, they can adapt quickly to a compl…