Durlav Sonowal
Papers
1
Total Citations
11
H-Index
1
About
Durlav Sonowal is a researcher whose work bridges robotics and human behavior, with a primary focus on developing intelligent navigation systems for mobile robots operating in unknown, dynamic environments. His most-cited paper, "Mobile Robot Navigation in Unknown Dynamic Environment Inspired by Human Pedestrian Behavior" (2018, 11 citations), introduces a novel approach that mimics how humans naturally navigate crowded or unpredictable spaces—such as avoiding collisions, anticipating movement, and adapting paths in real time. This bio-inspired strategy enhances robot autonomy and safety, offering practical solutions for applications in service robotics, autonomous vehicles, and industrial automation. Sonowal’s contributions are particularly valuable for advancing human-robot interaction, as they enable machines to move more naturally alongside people. While his citation count reflects a growing interest in this niche area, his work stands out for its interdisciplinary insight, merging cognitive science with engineering. By drawing on pedestrian behavior patterns, Sonowal provides a framework that is both computationally efficient and intuitively human-like, marking a meaningful step toward more adaptive and socially aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1