Mohd Hafiz Fazalul Rahiman
Papers
2
Total Citations
37
H-Index
2
About
Mohd Hafiz Fazalul Rahiman is a leading researcher in autonomous mobile robotics, specializing in navigation, path planning, and obstacle avoidance for unknown and dynamic environments. His work bridges classical control systems and modern artificial intelligence, with a particular focus on integrating sensor technologies like GPS and 2D LiDAR with advanced learning algorithms. Among his most impactful contributions is a seminal 2009 paper on mobile robot navigation using GPS and an obstacle avoidance system with a commanded loop daisy chaining method, which has garnered 23 citations and laid foundational work for agricultural and industrial robotics. More recently, his 2023 study on "2D LiDAR Based Reinforcement Learning for Multi-Target Path Planning in Unknown Environments" (14 citations) represents a significant advance, demonstrating how Q-learning can overcome the limitations of traditional global path planners in unstructured settings. This work highlights his ability to merge reinforcement learning with real-world sensor data, enabling robots to adaptively navigate without pre-mapped environments. Rahiman’s research is notable for its practical impact on autonomous systems, from military to agricultural applications, and his ongoing contributions continue to shape the future of intelligent, self-navigating machines.
Research Focus
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Top Papers
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