Papers
4
Total Citations
31
H-Index
3
About
Uzair Khan’s research lies at the intersection of bio-inspired robotics and legged locomotion, with a focus on developing natural, efficient movement strategies for both snake robots and bipedal systems. His most cited work, “Serpentine and Rectilinear Motion Generation in Snake Robot Using Central Pattern Generator with Gait Transition” (16 citations), introduces a biologically inspired control framework that enables smooth gait transitions—a critical step toward more adaptable and agile snake robots. In humanoid locomotion, Khan has made significant contributions by modeling and analyzing natural oscillation gaits, as seen in his papers on biped walking and jogging (totaling 15 citations across three related works). Notably, his 2016 study on compass-gait biped robots presents a novel continuous mathematical model that smooths the discontinuities inherent in foot impact, offering a more tractable framework for testing new control strategies. This work addresses a long-standing challenge in legged robotics: the hybrid dynamics that make traditional models difficult to analyze. Through his focus on natural, oscillator-driven gaits and seamless gait transitions, Khan is helping to bridge the gap between biological movement and robotic efficiency, laying groundwork for more fluid and resilient walking robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2Natural Oscillation Gait in Humanoid Biped Locomotion9 citations · 2019
- 3Natural gait analysis for a biped robot: jogging vs. walking4 citations · 2019
- 4Natural oscillation in compass-gait biped robots2 citations · 2016