Papers
7
Total Citations
85
H-Index
5
About
Haijun Han is a leading researcher in the field of robotic tactile sensing and intelligent manipulation, with a particular focus on sensor design and motion optimization for industrial robots. His most influential work, a 2016 study on a novel tactile sensor using electromagnetic induction for stick-slip interaction detection (32 citations), has been foundational for enabling robots to achieve stable grasping and dexterous manipulation by sensing real-time contact states. Han has further advanced the field by developing flexible tactile sensors that integrate piezoresistive thin films for three-dimensional force detection (2022, 8 citations) and hybrid sensors combining piezoresistive and electromagnetic principles (2022, 17 citations). Beyond sensing, his contributions extend to energy-optimal trajectory planning for high-load palletizing robots (2017, 18 citations), addressing critical efficiency challenges in industrial automation. Han’s work on dynamic characteristic analysis for structure optimization (2016, 5 citations) and novel cross-coupled synchronizing control for trajectory tracking (2015, 2 citations) demonstrates his comprehensive approach to improving robot performance. His integrated LuGre/Beam Network Model for soft-solid contact interactions (2015, 3 citations) provides a theoretical framework for understanding friction dynamics in robotic systems. Through this body of work, Han has established himself as a key innovator in tactile sensing and motion control, with his research directly impacting the development of more capable and efficient industrial robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Method of Energy‐Optimal Trajectory Planning for Palletizing Robot18 citations · 2017
- 3
- 4
- 5
- 6
- 7