Papers
1
Total Citations
2
H-Index
1
About
Haiwei Han is a robotics researcher whose work focuses on intelligent trajectory planning and cooperative control for robotic manipulators, particularly in complex, real-world manipulation tasks. His key research areas include multi-objective optimization, human-robot collaboration, and the control of flexible objects using dual-arm robotic systems. Han’s major contribution is the development of an improved multi-objective particle swarm optimization (MOPSO) algorithm for trajectory planning, which addresses the critical challenge of payload oscillations and joint impact when transporting flexible objects, such as cables, with master-secondary cooperative control strategies. This work, published in 2025, has already garnered early citations, signaling its relevance to advancing industrial automation and robotic dexterity. By integrating optimization techniques with robotic control, Han’s research offers practical solutions for reducing mechanical stress and improving precision in manufacturing and assembly processes. His achievements highlight a promising trajectory in robotics, with potential applications in logistics, automotive, and electronics industries where handling non-rigid materials is essential.
Research Focus
Key Achievements
Top Papers
- 1