Papers
17
Total Citations
187
H-Index
9
About
Nima Shafii is a leading researcher in humanoid robotics, whose work bridges the gap between simulated locomotion and real-world robotic dexterity. His core research areas include bipedal walking control, omnidirectional locomotion, and robotic grasping. Shafii pioneered the use of Truncated Fourier Series (TFS) combined with evolutionary algorithms—such as Particle Swarm Optimization and Genetic Algorithms—to generate stable, energy-efficient gaits for humanoid robots, a method that bypasses the need for precise ZMP modeling. His highly cited 2011 paper on biped walking using coronal and sagittal movements (26 citations) and his 2010 work on TFS-based evolution (19 citations) established foundational techniques for dynamic balance. He further advanced the field by optimizing hip height movement for faster walking (19 citations) and developing omnidirectional walking with compliant inverted pendulum models (17 citations). In manipulation, Shafii contributed to object view recognition and template matching for grasping (22 citations), as well as skill-based architectures for logistics tasks. His work has been validated on real platforms, including soccer humanoid robots, demonstrating a rare transition from simulation to physical hardware. With over 150 total citations, Shafii’s contributions continue to influence both locomotion and grasping in autonomous robotics.
Research Focus
Key Achievements
Top Papers
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- 5Omnidirectional Walking and Active Balance for Soccer Humanoid Robot17 citations · 2013
- 6Humanoid Behaviors: From Simulation to a Real Robot16 citations · 2011
- 7Object Learning and Grasping Capabilities for Robotic Home Assistants11 citations · 2017
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- 10Omnidirectional Walking with a Compliant Inverted Pendulum Model8 citations · 2014