Papers
9
Total Citations
74
H-Index
5
About
Xianlun Wang is a robotics researcher whose work spans adaptive control, robot kinematics, path planning, and computer vision — core pillars of modern intelligent manufacturing systems. His early contributions focused on robotic deburring, where he developed adaptive impedance-based control algorithms capable of detecting burrs and cavities on workpiece surfaces, overcoming the limitations of conventional force control methods that merely replicated surface imperfections. These foundational papers from 2006, which together have accumulated over 20 citations, also incorporated fuzzy logic to achieve more intelligent compliance control. Wang further broadened his impact through kinematic modeling, proposing a simplified inverse kinematics solution for 6R industrial robots that elegantly sidesteps complex matrix operations. His 2019 work on vision-based coordinated motion for dual-arm robots reflects a growing engagement with perception-driven manipulation, while more recent contributions address path planning using velocity potential fields to reduce manipulator oscillation and lightweight visual odometry for autonomous mobile robots. Collectively, Wang's body of work — totaling over 70 citations — charts a trajectory from precision manufacturing automation toward the intelligent, perception-aware robotic systems increasingly demanded by modern collaborative manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1Adaptive Control of Robotic Deburring Process Based on Impedance Control15 citations · 2006
- 2A New Method for Solving Inverse Kinematics of an Industrial Robot14 citations · 2012
- 3A Vision-Based Coordinated Motion Scheme for Dual-Arm Robots12 citations · 2019
- 4
- 5An Adaptive algorithm for robotic deburring based on impedance control6 citations · 2006
- 6Intelligent Compliance Control for Robotic Deburring Using Fuzzy Logic5 citations · 2006
- 7
- 8A Lightweight Visual Odometry Based on LK Optical Flow Tracking4 citations · 2023
- 9