Papers
15
Total Citations
134
H-Index
7
About
Abdul Md Mazid is a robotics and automation researcher whose work bridges tactile sensing, intelligent grasping, and agricultural automation. His most influential contribution is the development of a novel opto-tactile sensor for assessing object surface texture, first introduced in his 2006 paper (26 citations), which enables robots to identify surface patterns and support quality assurance tasks. Building on this, he demonstrated surface texture pattern recognition using support vector machines (15 citations) and developed a tactile sensor-based intelligent grasping system (13 citations) capable of monitoring slip during robotic manipulation. His method for controlling grip force and slippage (12 citations) offers a simple, robust, and low-cost solution for reliable object handling. Mazid also extended his expertise to agricultural robotics, co-authoring a 2025 overview on intelligent weed management using aerial image processing and precision herbicide spraying (10 citations). His work on depth sensors for fruit packaging robots (8 citations) provides an affordable alternative for pick-and-place applications. With over 100 total citations across his top papers, Mazid’s research has advanced both industrial automation and precision agriculture, demonstrating a consistent focus on sensor-driven, intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1A Robotic Opto-tactile Sensor for Assessing Object Surface Texture26 citations · 2006
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- 4Tactile sensor based intelligent grasping system13 citations · 2017
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- 7A depth sensor to control pick-and-place robots for fruit packaging8 citations · 2012
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