Aimin Jiang
Papers
5
Total Citations
204
H-Index
5
About
Aimin Jiang is a robotics researcher whose work bridges intelligent control, human-robot interaction, and assistive technology. His primary research areas include mobile robot trajectory tracking, visual tracking, and interactive systems for motor learning. Jiang’s most impactful contribution is his work on trajectory tracking for omni-directional wheeled mobile robots using model predictive control (MPC), a paper that has garnered 159 citations and demonstrates how MPC can enable precise, independent rotation and translation in three-mecanum-wheel configurations—a significant advance over non-holonomic platforms. He has also made notable contributions to visual tracking, developing a multi-channel feature spatio-temporal context learning method that addresses challenges like occlusion and illumination changes (17 citations). In a compelling application of robotics to healthcare, Jiang designed an interactive training platform for children with autism spectrum disorder (ASD), using a NAO humanoid robot to facilitate motor learning through imitation and speech instructions (16 citations). His work on robust direction-of-arrival estimation using acoustic vector sensors (7 citations) further showcases his versatility, targeting real-world challenges in service robotics and smart homes. Jiang’s research consistently demonstrates a commitment to advancing both the theoretical foundations and practical applications of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multi-Channel Features Spatio-Temporal Context Learning for Visual Tracking17 citations · 2017
- 3
- 4Learning a robust DOA estimation model with acoustic vector sensor cues7 citations · 2017
- 5Movement imitation underlying coaching platform for children with ASD5 citations · 2015