Papers
2
Total Citations
39
H-Index
2
About
Kunkun Cui is a robotics researcher whose work focuses on the critical challenges of sensor accuracy and motion planning for advanced robotic manipulators. His primary research areas include multi-dimensional force/torque sensing, payload identification, and path planning for hyper-redundant systems. Cui’s most impactful contribution is a novel approach to gravity and inertial compensation for six-dimensional force/torque sensors, which addresses a fundamental problem in robot contact operations. By developing a fast and robust trajectory design method for payload identification, his work ensures that when robots handle heavy loads or move at high speeds, the sensor readings remain accurate—a key requirement for precise assembly, machining, and human-robot collaboration. This paper has garnered 29 citations, reflecting its practical significance. Additionally, Cui has advanced the field of hyper-redundant manipulators—snake-like robots with many degrees of freedom designed for narrow spaces like aerospace interiors or disaster rubble. His use of NURBS (Non-Uniform Rational B-Splines) for path planning solves the complex dual challenge of obstacle avoidance and inverse kinematics selection, enabling these flexible robots to navigate confined environments effectively. Through these contributions, Cui is helping to make robots more perceptive and adaptable in real-world, constrained settings.
Research Focus
Key Achievements
Top Papers
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