Papers
8
Total Citations
70
H-Index
5
About
Yuancheng Li is a pioneering researcher at the intersection of robotics, brain-computer interfaces (BCI), and human augmentation. His work primarily focuses on intelligent path planning for mobile robots, alertness estimation in unmanned systems, and the development of supernumerary robotic limbs (SRLs)—wearable robotic appendages that enhance human capabilities. Li’s most cited paper, “CLSQL: Improved Q-Learning Algorithm Based on Continuous Local Search Policy for Mobile Robot Path Planning” (2022, 21 citations), introduces a novel algorithm that significantly accelerates robot navigation by reducing blind search steps. He has also made notable contributions to BCI, including a coloring and timing interface for nursing bed robots and NAO robot limb control via motor imagery EEG. In the emerging field of SRLs, Li has designed reconfigurable robotic legs (SuperLegs) and leader-follower controllers for load-carrying, addressing human-induced disturbances and safe interaction. His work on alertness estimation using brain network connection parameters (2021, 14 citations) has implications for underground security robots. With a growing citation record and recent publications in 2024–2025, Li is shaping the future of human-robot collaboration and assistive robotics.
Research Focus
Key Achievements
Top Papers
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- 2Alertness Estimation Using Connection Parameters of the Brain Network14 citations · 2021
- 3A coloring and timing brain-computer interface for the nursing bed robot11 citations · 2021
- 4NAO Robot Limb Control Method Based on Motor Imagery EEG9 citations · 2020
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