Wasif Muhammad
Papers
9
Total Citations
88
H-Index
5
About
Wasif Muhammad is a robotics researcher whose work sits at the intersection of autonomous navigation, biomimetic perception, and human-robot interaction. His primary research areas include multi-sensor fusion for self-localization, simultaneous localization and mapping (SLAM) for unmanned aerial and ground vehicles, and neural models of sensory-motor control inspired by biological vision and audition. Muhammad’s most cited work, “Multi-sensor fusion for underwater robot self-localization using PC/BC-DIM neural network” (31 citations), introduces a bio-inspired approach to positioning in GPS-denied underwater environments. He has also made notable contributions to autonomous lawn-mower robot control (18 citations) and neural modeling of binocular saccade planning and vergence control (14 citations). His research extends to driverless car vSLAM, binaural auditory perception for humanoid robots, and human-like arm movement generation using Bayesian inference. Across his publications, Muhammad consistently leverages neural network architectures to solve real-world robotics challenges, particularly in environments where traditional GPS and sensing systems fail. His work demonstrates a sustained focus on making autonomous systems more adaptive, perceptive, and biologically plausible.
Research Focus
Key Achievements
Top Papers
- 1
- 2Design and implementation of autonomous Lawn-Mower Robot controller18 citations · 2011
- 3A neural model of binocular saccade planning and vergence control14 citations · 2015
- 4A Neural Model of Coordinated Head and Eye Movement Control8 citations · 2016
- 5Comparative Study of SLAM Techniques for UAV6 citations · 2022
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