Mohd Khair Hassan
Papers
5
Total Citations
24
H-Index
2
About
Mohd Khair Hassan is a robotics researcher whose work lies at the intersection of tactile sensing, autonomous navigation, and intelligent control systems. His research addresses fundamental challenges in robotic manipulation and mobile robot autonomy, with a particular focus on enabling robots to interact safely and effectively with dynamic, unpredictable environments. Hassan’s most cited work, "Slip detection with accelerometer and tactile sensors in a robotic hand model" (2015, 11 citations), investigates the physical force interactions between tactile sensors and objects during gripping operations, developing methods to characterize and detect object slipping—a critical capability for reliable robotic manipulation. He has also made significant contributions to autonomous navigation, proposing a collision prediction framework using Genetic Network Programming with Reinforcement Learning (GNP-RL) for mobile robots chasing moving targets in unknown dynamic environments (2017, 9 citations), and developing a real-time dynamic path planning algorithm for intelligent robot cars (2017, 2 citations). More recently, Hassan has explored fractional-order PID controller tuning for robotic manipulators using genetic algorithms (2024) and stochastic mapping analysis for Automated Guided Vehicles in ROS environments (2025). His work bridges theoretical control methods with practical robotic applications, contributing to safer, more adaptive autonomous systems capable of operating in complex real-world settings.
Research Focus
Key Achievements
Top Papers
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- 5Stochastic Mapping Analysis for Automated Guided Vehicles in ROS1 citations · 2025