Papers
30
Total Citations
648
H-Index
13
About
Hangxin Liu is a robotics and AI researcher whose work spans human-robot interaction, robot learning, manipulation, and augmented reality interfaces. Best known for his influential 2019 paper "A Tale of Two Explanations" (132 citations), Liu has made foundational contributions to explainable AI in robotics, demonstrating how structured explanations can significantly enhance human trust in autonomous systems — a critical concern as robots move into high-stakes environments. His research on augmented reality-based knowledge patching (73 citations) pioneered intuitive methods for humans to diagnose and correct robot behavior through tools like Microsoft HoloLens, while his imitation learning work on multi-stage manipulation tasks (66 citations) advanced the field of dexterous robotic control. More recently, Liu has pushed boundaries in tactile sensing, developing robotic hands with high-resolution touch capabilities (36 citations), and in scene understanding, proposing contact graph representations for sequential manipulation planning. His VRGym testbed further reflects a commitment to realistic, scalable human-robot interaction research. With over 400 cumulative citations across a decade of work, Liu represents a versatile and deeply impactful voice in modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1A tale of two explanations: Enhancing human trust by explaining robot behavior132 citations · 2019
- 2Interactive Robot Knowledge Patching Using Augmented Reality73 citations · 2018
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- 5Sequential Manipulation Planning on Scene Graph34 citations · 2022
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- 7Scene Reconstruction with Functional Objects for Robot Autonomy26 citations · 2022
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- 9VRGym25 citations · 2019
- 10Human-Robot Interaction in a Shared Augmented Reality Workspace21 citations · 2020