Shoaib Mohd Nasti
Papers
6
Total Citations
25
H-Index
3
About
Shoaib Mohd Nasti is an emerging researcher specializing in mobile robotics, autonomous navigation, and artificial intelligence-driven control systems. His work centers on solving one of robotics' most persistent challenges: enabling mobile robots to navigate safely and efficiently through complex, dynamic environments. Nasti's early contribution, "Obstacle Avoidance during Robot Navigation in Dynamic Environment using Fuzzy Controller" (2019), demonstrated the superiority of fuzzy logic controllers over traditional pure pursuit methods for collision-free navigation, garnering 7 citations and establishing his foundational expertise. He has since expanded into deep reinforcement learning, proposing an improved Twin Delayed Deep Deterministic Policy Gradient (TD3) framework for mapless robot navigation in unknown environments. His comprehensive review papers on AI-enhanced navigation strategies and path planning techniques, each accumulating 6 citations shortly after publication in 2024, reflect his commitment to synthesizing advancements across the field for the broader research community. Notably, Nasti has also explored real-world applications, proposing an autonomous robot-based logistics framework for Hajj pilgrim services. With a growing publication record and cross-disciplinary applications, he represents a promising voice in intelligent robotics research.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5Framework for Logistics During Hajj Using Autonomous Mobile Robots2 citations · 2024
- 6