Abdulaziz Shamsah
Papers
9
Total Citations
71
H-Index
4
About
Abdulaziz Shamsah is a robotics researcher specializing in bipedal locomotion, safe navigation, and task and motion planning (TAMP) for legged robots. His work sits at the intersection of formal methods, control theory, and machine learning, with a focus on enabling humanoid and bipedal robots to operate reliably in complex, real-world environments. Shamsah's most influential contribution is his hierarchically integrated TAMP framework for bipedal locomotion in partially observable environments — combining linear temporal logic for high-level reactive planning with physics-based motion planners to provide multi-level safety guarantees. This line of work has accumulated over 48 citations across multiple publications. He has also pioneered socially aware bipedal navigation, introducing zonotope-based neural network architectures for real-time model predictive control in human-crowded settings — an underexplored but increasingly critical challenge in human-robot coexistence. Earlier work on tailed bipedal hopping robots demonstrates his grounding in hardware-informed, analytically-guided design. More recently, his co-authored survey on humanoid locomotion and manipulation synthesizes the state of the field across control, planning, and learning. Collectively, Shamsah's research advances the safety, adaptability, and social awareness of next-generation legged robots navigating uncertain terrain and dynamic human environments.
Research Focus
Key Achievements
Top Papers
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- 4Analytically-Guided Design of a Tailed Bipedal Hopping Robot5 citations · 2018
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