Xinjun Sheng
Papers
44
Total Citations
715
H-Index
13
About
Dr. Xinjun Sheng is a leading researcher at the intersection of robotics, human-machine interaction, and intelligent control systems. His work primarily focuses on advancing assistive robotics, autonomous navigation, and bio-signal processing, with a particular emphasis on non-invasive brain-computer interfaces (BCIs) and surface electromyography (sEMG) for prosthetic control. Dr. Sheng’s major contributions include developing shared control frameworks that integrate BCI with computer vision for robotic arm manipulation (103 citations), and pioneering sEMG image-driven torque estimation for multi-degree-of-freedom wrist movements (48 citations). He has also made significant strides in autonomous robotics, proposing novel algorithms such as the artificially weighted spanning tree coverage for decentralized flying robots (50 citations) and active sense-and-avoid systems for dynamic environments (42 citations). His work on cooperative transportation using mobile manipulators (41 citations) and multi-material 3D printing of soft crawling robots (46 citations) further demonstrates his versatility. Notably, his research on ball motion control for table tennis robots using deep reinforcement learning (37 citations) showcases the application of AI in real-time robotic systems. With over 485 citations across his top ten papers, Dr. Sheng’s innovative approaches to human-robot collaboration and autonomous systems continue to shape the future of intelligent robotics.
Research Focus
Key Achievements
Top Papers
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- 6An Active Sense and Avoid System for Flying Robots in Dynamic Environments42 citations · 2021
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- 9Multi-DoF continuous estimation for wrist torques using stacked autoencoder34 citations · 2019
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