Papers
8
Total Citations
302
H-Index
5
About
Haojian Zhang is a leading researcher at the intersection of robotics, artificial intelligence, and intelligent manufacturing, with a focus on enabling robots to operate autonomously in complex, real-world environments. His foundational work on path planning, particularly the development of an improved Rapidly-exploring Random Tree (RRT) algorithm for industrial robots in complex environments, has garnered 188 citations and is critical for advancing autonomous manufacturing. Zhang has also made significant contributions to high-speed precision robotics, proposing a time-optimal trajectory planning method using quintic Pythagorean-Hodograph curves for Delta parallel robots (63 citations). More recently, his research has expanded into intelligent assistive and medical robotics. He has pioneered human motion forecasting networks (MoFCNet) using IMU data for hip assistive exoskeletons and designed a novel redundant parallel mechanism for long bone fracture reduction. In the realm of robotic perception and manipulation, Zhang introduced the task of Class Incremental Robotic Pick-and-Place and developed instance-augmented networks for 3D instance segmentation in cluttered scenes. His work is characterized by a seamless integration of theoretical innovation with practical, high-impact applications, positioning him as a key figure in the next generation of autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 6IAN: Instance-Augmented Net for 3D Instance Segmentation3 citations · 2023
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