Majid Sadedel
Papers
19
Total Citations
172
H-Index
9
About
Majid Sadedel is a robotics researcher whose work spans humanoid locomotion, dynamic modeling, rehabilitation robotics, and autonomous robot navigation. He has made significant contributions to the field of bipedal walking, particularly in developing optimization frameworks that generate efficient and stable gait patterns for humanoid robots. His most cited work, "Optimal Gait Planning for Humanoids with 3D Structure Walking on Slippery Surfaces" (2015, 32 citations), pioneered methods for minimizing friction demands during walking—a critical challenge for real-world robot deployment. Alongside this, his research into full dynamic modeling of humanoids under general robot-environment interaction (18 citations) established versatile foundations for simulating complex locomotion phases. Sadedel has also explored toe-joint mechanics, demonstrating how passive toe structures can enhance humanoid performance without prohibitive hardware costs. His later work broadened into autonomous hexapod navigation using hybrid automata (16 citations), reinforcement learning for hopping robot balance, and neural network-based inverse kinematics for wrist rehabilitation robots (12 citations). This diverse yet cohesive body of research, accumulating over 140 citations, reflects his sustained influence across legged robotics, biomechanical modeling, and intelligent control systems—making his work essential reading for robotics students and engineers alike.
Research Focus
Key Achievements
Top Papers
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- 7Online adaptation for humanoids walking on uncertain surfaces11 citations · 2017
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