Papers
10
Total Citations
154
H-Index
7
About
Long Kang is a robotics researcher whose work spans soft robotics, robotic grippers, underactuated mechanisms, and surgical robotics. He has made significant contributions to the design and implementation of innovative robotic gripping systems, particularly advancing how robots interact with and manipulate objects across industrial and medical contexts. Kang's most influential work, "A 3D-Printed Fin Ray Effect Inspired Soft Robotic Gripper with Force Feedback" (2021, 54 citations), demonstrated a breakthrough approach to soft robotic gripping by leveraging bio-inspired design principles and additive manufacturing to overcome longstanding limitations in control and tactile feedback. His complementary research into multi-function and underactuated grippers — including work on linkage-driven fingers and adaptive three-fingered systems — has helped address the growing industrial demand for reliable, versatile pick-and-place automation in warehouse and fulfillment environments, collectively attracting dozens of citations. Beyond grippers, Kang has explored wrist mechanism kinematics, continuum robot modeling for colonoscopy, and trans-oral surgical robotics, reflecting a broad commitment to advancing dexterous robotic systems in both industrial and medical settings. His 2019 review of dimension inhomogeneity in robotics further demonstrates his interest in rigorous performance evaluation frameworks. With over 150 cumulative citations, Kang's research represents a meaningful and growing contribution to the field of applied robotics and mechanism design.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Design of a 3-DOF Linkage-Driven Underactuated Finger for Multiple Grasping14 citations · 2019
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- 6A Three-Fingered Adaptive Gripper with Multiple Grasping Modes8 citations · 2021
- 7Review of Dimension Inhomogeneity in Robotics7 citations · 2019
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- 9A robot design for trans-oral surgery3 citations · 2014
- 10