Mohammad Nuh

Sepuluh Nopember Institute of Technology

Papers

5

Total Citations

36

H-Index

3

About

Mohammad Nuh is a pioneering researcher in disaster robotics and assistive technology, whose work bridges the gap between autonomous navigation and human-centered applications. His primary research areas include SLAM (Simultaneous Localization and Mapping), path planning, and behavior-based navigation for mobile robots operating in hazardous environments. Nuh’s most cited work, “Application SLAM and Path Planning using A-Star Algorithm for Mobile Robot in Indoor Disaster Area” (24 citations), introduces a two-dimensional mapping system that enables robots to autonomously navigate disaster zones, a critical contribution for search-and-rescue operations. He further advances this field with “Disaster Swarm Robot Development” (5 citations), exploring multi-robot coordination for earthquake and tsunami response, and “Disaster Robot Navigation using Behavior-based Systems” (2 citations), which proposes adaptive locomotion for unpredictable terrains. Beyond disaster robotics, Nuh innovates in biomedical engineering, developing EMG signal analysis for neck muscles to aid laryngectomee communication, and in assistive robotics, creating knowledge-based systems to enhance cognitive abilities in children with intellectual disabilities. His interdisciplinary work, spanning from autonomous mapping to human-robot interaction, demonstrates a profound commitment to leveraging robotics for societal benefit, making him a notable figure in both disaster response and inclusive technology development.

Research Focus

Key Achievements

3
H-Index
5
Papers
36
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Application SLAM and Path Planning using A-Star Algorithm for Mobile Robot in Indoor Disaster Area
24 citations · 2018
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Sepuluh Nopember Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago