Issa W. AlHmoud
Papers
5
Total Citations
19
H-Index
4
About
Issa W. AlHmoud is a leading researcher at the intersection of autonomous robotics, digital twin technology, and human-robot collaboration. His work focuses on developing intelligent navigation systems that enable robots to operate safely and efficiently in complex indoor environments. AlHmoud’s major contributions include the integration of deep learning-based object detection with 3D depth cameras for collision avoidance, as demonstrated in his highly cited 2025 paper, and the design of multi-sensor systems combining cameras and IMUs for precise path correction. He has also pioneered frameworks for digital twin mixed-reality applications, enabling bidirectional human-robot collaboration in manufacturing contexts such as forming double curvature plates. His research on real-time VR-enabled digital twins for multi-user interaction in Industry 4.0 represents a significant step forward in industrial automation. With multiple papers each garnering 4-5 citations shortly after publication, AlHmoud’s work is rapidly gaining recognition for its practical impact on indoor robotics navigation and smart manufacturing systems.
Research Focus
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Top Papers
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