Sheng-Ru Xiao
Papers
6
Total Citations
48
H-Index
6
About
Sheng-Ru Xiao is a robotics researcher whose work centers on humanoid robot locomotion, balance control, and path planning. His major contributions include developing a novel obstacle avoidance method for robot arms using Non Uniform Rational B-splines (NURBS), which introduced a safety formula to prevent collisions. Xiao has also made significant advances in bipedal walking, proposing the Three-mass Linear Inverted Pendulum plus Flywheel Model (TLIPFM) to more accurately simulate humanoid gait by accounting for mass distribution and angular momentum. His research on push recovery balance control, implemented in real-time on FPGA chips, addresses how robots can maintain stability when pushed by external forces. Xiao’s work on Q-learning for straightforward gait patterns and ROS-based pose control systems further demonstrates his focus on practical, real-world robotic applications. With over 48 citations across his most-cited papers, his studies on balance control and trajectory generation have influenced the development of more resilient humanoid robots. Notably, his 2017 paper on path planning remains his most cited work, highlighting his early impact in robotics.
Research Focus
Key Achievements
Top Papers
- 1Path planning and obstacle avoidance approaches for robot arm13 citations · 2017
- 2ROS-Based Humanoid Robot Pose Control System Design8 citations · 2018
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