Liandong Zhang
Papers
11
Total Citations
177
H-Index
6
About
Liandong Zhang is a pioneering researcher in robotics and neuromorphic engineering, whose work bridges the gap between biological intelligence and autonomous systems. His most impactful contribution is the development of an artificial neural pathway using a memristor synapse for optically mediated motion learning (125 citations), a breakthrough that enables robots to mimic biological learning, memory, and cognition for self-optimizing behavior. Zhang is also renowned for his innovative use of geodesics in robotic trajectory planning—a mathematical framework he applied to optimize path planning for the Kuka youBot arm, humanoid biped gait, and three-dimensional walking patterns. His geodesic-based methods minimize energy consumption and landing impact, advancing efficient locomotion in humanoid robots. Additionally, Zhang has contributed to adaptive compliant control for biped feet with elastic energy storage, reducing impact forces and conserving energy. His work on 3D object recognition using Kernel PCA for twist-lock grasping demonstrates his focus on practical automation solutions. With a career spanning over a decade, Zhang’s research has laid foundational principles for intelligent, energy-efficient robots, earning recognition for its interdisciplinary impact on robotics, control systems, and neuromorphic computing.
Research Focus
Key Achievements
Top Papers
- 1
- 2Kuka youBot arm shortest path planning based on geodesics10 citations · 2013
- 3
- 4Optimal energy gait planning for humanoid robot using geodesics7 citations · 2010
- 5
- 6Robot Optimal Trajectory Planning Based on Geodesics6 citations · 2007
- 7
- 8
- 9Robotic arm force sensing interaction control3 citations · 2012
- 10Human and humanoid robot interaction using 6-axis force torque sensors2 citations · 2012