Papers
8
Total Citations
86
H-Index
6
About
Aisha Muhammad is a robotics and autonomous systems researcher whose work centers on mobile robot navigation, path planning, and intelligent control algorithms. She has made significant contributions to the field through both comprehensive reviews and original algorithmic development, accumulating over 85 citations across her published works. Muhammad's most impactful contribution is her systematic bibliometric review of path planning methods for mobile robots (2020, 20 citations), which has become a key reference for researchers entering the field. Building on this foundation, she developed the Generalized Laser Simulator (GLS) algorithm, a novel approach enabling mobile robots to navigate efficiently through constrained two-dimensional environments while avoiding static and dynamic obstacles — work that has garnered consistent recognition across multiple publications. Her 2022 comparative simulation study benchmarking A*, GLS, RRT, and PRM algorithms provides the research community with valuable practical insights into algorithmic performance trade-offs. Beyond navigation, Muhammad has demonstrated breadth through her structural analysis of knuckle joint optimization and, most recently, sensor fusion-based localization for robots in complex road environments. Her body of work reflects a researcher steadily advancing autonomous robotics from theoretical review toward practical, deployable solutions, making her publications essential reading for students and engineers working in robot autonomy and intelligent navigation systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Novel Algorithm for Mobile Robot Path Planning in Constrained Environment16 citations · 2021
- 3A review: On Intelligent Mobile Robot Path Planning Techniques13 citations · 2021
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- 5
- 6Transient Analysis And Optimization Of A Knuckle Joint9 citations · 2019
- 7A Novel Algorithm for mobile robot path planning4 citations · 2021
- 8