Papers
9
Total Citations
30
H-Index
3
About
Mudasar Basha is a dedicated researcher specializing in FPGA-based robotics, autonomous navigation, and human-robot interaction, with a growing body of work that bridges embedded hardware design and intelligent robotic systems. His research consistently leverages Field Programmable Gate Arrays (FPGAs) as a hardware backbone for developing smarter, more responsive robotic platforms suited to real-world indoor environments. Among his notable contributions, his 2020 paper on IoT-controlled FPGA robots garnered 6 citations, establishing foundational work in Wi-Fi-enabled autonomous navigation. He has further advanced the field through innovative algorithms such as the Grid Flex-Graph Exploration (GFGE) method for adaptive robotic mapping and hardware-scheme-based approaches to multi-robot collision prevention. His work on door detection using Sobel edge algorithms highlights a meaningful commitment to assistive technology for elderly and physically disabled individuals. More recently, Basha has extended his expertise into autonomous driving, exploring convolutional neural networks for traffic sign recognition. Across his publications, accumulating over 30 citations, he demonstrates a consistent drive to translate complex hardware-software integration into practical, human-centered robotic solutions, making his work increasingly relevant to students and engineers pursuing intelligent embedded systems research.
Research Focus
Key Achievements
Top Papers
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- 3A Inventive Method for Door Detection on FPGA Using Sobel Edge Algorithm4 citations · 2022
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- 8Deliberation of Robotic Services to Human kind using FPGA based Robot2 citations · 2019
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