Papers
17
Total Citations
186
H-Index
8
About
Minxiu Kong is a robotics researcher whose career spans over two decades of contributions to industrial robot systems, trajectory planning, and robot kinematics. Working at the intersection of mechanical engineering and control theory, Kong has made significant strides in solving some of the most persistent challenges in robotic motion optimization. His most-cited work, a 2023 paper on convex time-optimal trajectory planning with jerk constraints (37 citations), exemplifies his signature approach of combining B-spline representations with convex optimization to generate smooth, efficient robot trajectories — a thread that runs consistently through his research since at least 2013. His geometric solution to the forward kinematics of the H4 parallel robot (23 citations) demonstrated an elegant alternative to cumbersome algebraic methods, while early work on heavy-duty industrial robot control systems (20 citations) grounded his research in real-world engineering practice. Notably, Kong also contributed to medical robotics, co-developing the HIT-RAOTS orthopedic telesurgery system as early as 2005. His investigations into variable stiffness actuators, dual-robot collision detection, and point-cloud-based spray path planning further reflect a researcher of broad technical vision whose work continues to shape modern industrial robotics.
Research Focus
Key Achievements
Top Papers
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- 3Control system design for heavy duty industrial robot20 citations · 2012
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- 5A Robot-Assisted Orthopedic Telesurgery System15 citations · 2005
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- 7Application of orientation interpolation of robot using unit quaternion12 citations · 2013
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- 9A Spray Path Planning Algorithm based on 3D Point Cloud7 citations · 2019
- 10