Mominul Islam
Papers
1
Total Citations
6
H-Index
1
About
Mominul Islam is a researcher whose work lies at the intersection of robotics, tactile sensing, and intelligent manipulation. His key research areas include grasp force estimation, object slippage detection, and the application of neural networks to enhance robotic dexterity. In his notable 2008 paper, “Grasping Force Estimation Recognizing Object Slippage by Tactile Data Using Neural Network,” Islam addressed a critical challenge in industrial robotics: the lack of self-consciousness in machines that limits their ability to recognize and handle objects appropriately. By leveraging tactile data and neural network models, he proposed a method for estimating grasping force in real time, enabling robots to detect and respond to object slippage. This contribution is foundational for advancing the hierarchical and wider applications of manipulators and pick-and-place machines in dynamic environments. Though his most-cited work has garnered 6 citations, its impact is significant in the niche field of tactile-based robotic control, where precision and adaptability are paramount. Islam’s research continues to inform efforts to make robots more autonomous and reliable in handling tasks, bridging the gap between raw sensory input and intelligent action.
Research Focus
Key Achievements
Top Papers
- 1