Papers
12
Total Citations
167
H-Index
5
About
Saixuan Chen is a robotics researcher whose work sits at the intersection of medical robotics, collaborative robot control, and human-robot safety. Chen’s primary contributions include developing a precise positioning method for puncture robots using a PSO-optimized BP neural network algorithm (87 citations), which addresses the fundamental challenge of inverse kinematics in robot control. This work has direct applications in computer-assisted surgery, particularly for needle guidance and positioning. Chen also proposed a universal algorithm for sensorless collision detection of robot actuator faults (30 citations), enhancing robot safety in human-occupied environments, and developed a zero-moment control algorithm for direct teaching of collaborative robots (13 citations), enabling intuitive human-robot interaction through gravity and friction compensation. Additional work includes analytical inverse kinematics solutions for 6-DOF collaborative robots and adaptive threshold collision detection using fuzzy systems. Chen’s research is notable for its practical focus on medical robotics—specifically puncture procedures—and for advancing the safety and teachability of collaborative robots. With over 160 total citations, Chen’s work continues to influence the design of safer, more intuitive robotic systems for both industrial and clinical settings.
Research Focus
Key Achievements
Top Papers
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- 5Vision solution for an assisted puncture robotics system positioning8 citations · 2018
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- 8Multiple configurations for puncturing robot positioning3 citations · 2019
- 9MULTIPLE CONFIGURATIONS FOR PUNCTURING ROBOT POSITIONING2 citations · 2019
- 10Walking mechanism and kinematic analysis of humanoid robot2 citations · 2013