Papers
31
Total Citations
502
H-Index
11
About
Yanjiang Huang is a leading researcher in robotics, specializing in robot manipulation, human-robot interaction, and intelligent control systems. His work addresses critical challenges in industrial automation and assistive robotics, with a focus on dynamic parameter identification, kinematic control, and multi-robot coordination. Huang's most cited paper, "Dynamic Parameter Identification of Serial Robots Using a Hybrid Approach" (2022, 84 citations), advances model-based control for high-accuracy industrial robots, while his research on singularity avoidance in teaching-playback systems (2015, 49 citations) has practical implications for manufacturing. He has made significant contributions to dual-arm robot assembly, developing vision-guided and force/torque sensor-based methods for peg-in-hole tasks, as seen in his 2017 and 2020 papers (38 and 30 citations). Huang also explores bio-inspired robotics, including a novel cable-driven 7-DOF anthropomorphic manipulator (2020, 41 citations) for safe human-robot interaction, and sEMG-based motion estimation for human arm joint torque (2021, 38 citations; 2020, 24 citations). His work on multi-robot coordination in pick-and-place tasks (2014, 44 citations) and transfer nursing robots (2024, 15 citations) underscores his impact across both industrial and healthcare applications. With over 400 total citations, Huang's research is essential reading for those advancing robotic manipulation and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Dynamic Parameter Identification of Serial Robots Using a Hybrid Approach84 citations · 2022
- 2
- 3
- 4A Novel Cable-Driven 7-DOF Anthropomorphic Manipulator41 citations · 2020
- 5
- 6
- 7
- 8Vision-guided peg-in-hole assembly by Baxter robot25 citations · 2017
- 9
- 10