Papers
7
Total Citations
178
H-Index
5
About
Mingxuan Chen is a leading researcher in human-robot interaction (HRI), with a focus on making robots more intuitive, collaborative, and intelligent. His work spans natural HRI, human-swarm interaction, and augmented reality (AR)-based control systems. Chen’s major contributions include developing online robot teaching methods that enable natural communication between humans and robots, as well as multichannel interaction systems for controlling robot swarms through AR interfaces. His most cited paper, "Online Robot Teaching With Natural Human–Robot Interaction" (2018), has garnered 112 citations and addresses the need for collaborative robots in Industry 4.0. He has also advanced gesture- and pose-based programming frameworks and intelligent grasping techniques that integrate visual and voice inputs. With over 178 total citations across his key works, Chen’s research is shaping the future of flexible, human-centric automation. His recent work on multi-modal depth estimation continues to push boundaries, demonstrating his ongoing commitment to enhancing robot perception and interaction in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Online Robot Teaching With Natural Human–Robot Interaction112 citations · 2018
- 2A multichannel human-swarm robot interaction system in augmented reality26 citations · 2020
- 3A human–robot interface for mobile manipulator18 citations · 2018
- 4
- 5Intelligent grasping with natural human-robot interaction8 citations · 2017
- 6A Human-swarm Interaction Method Based on Augmented Reality3 citations · 2018
- 7Multi-modal Scene Global Fusion Framework for Enhanced Depth Estimation1 citations · 2025