Junshen Chen
Swansea University, University of Plymouth, Cardiff University
Papers
10
Total Citations
120
H-Index
7
About
Junshen Chen is a robotics researcher whose work sits at the intersection of human-robot interaction, teleoperation, and intelligent control systems. With a strong focus on making robot control more intuitive and immersive, Chen has made notable contributions to the development of advanced teleoperation interfaces that integrate emerging technologies such as mixed reality, inertial measurement units, and neural network-based learning. His highly cited work on immersive teleoperation interfaces and IMU-based motion capture using MYO armbands—each garnering nearly 20 citations—demonstrates his commitment to bridging the gap between human intent and robotic action. Chen has explored neural learning-enhanced control strategies applied to platforms such as the Baxter robot and humanoid dual-arm systems, combining visual servoing with skill transfer to improve robot dexterity and adaptability. His research extends into physiological signal integration, redundant manipulator obstacle avoidance, and accessible hardware solutions including 3D-printed robotic limbs and data gloves. Collectively accumulating over 120 citations, Chen's body of work reflects a holistic approach to human-robot collaboration, making robotics more responsive, user-friendly, and applicable across industrial and assistive domains.
Research Focus
Key Achievements
Top Papers
- 1Development of an Immersive Interface for Robot Teleoperation20 citations · 2017
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- 4Development of a user experience enhanced teleoperation approach17 citations · 2016
- 5Development of a mixed reality based interface for human robot interaciotn14 citations · 2017
- 6Development of a physiological signals enhanced teleoperation strategy13 citations · 2015
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- 93D Printed Data Glove Design for VR Based Hand Gesture Recognition4 citations · 2018
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