Navid Zarrabi
Papers
2
Total Citations
6
H-Index
2
About
Navid Zarrabi is a robotics researcher focused on advancing autonomous mobile robot navigation in human-centric environments. His work centers on two critical challenges: improving robot localization accuracy and enhancing path planning through intelligent, adaptive systems. In his 2019 study on robot localization performance, Zarrabi systematically evaluated four distinct SLAM approaches using a ROS-based differential drive platform in homogeneous indoor settings, providing practical insights into odometry-based localization—a foundational issue for mobile robotics. His more recent 2022 work introduces a novel approach to path planning by dynamically reconfiguring costmap parameters using Fuzzy controllers, enabling robots to navigate complex environments with greater intuition and safety when operating alongside humans. While his citation counts (4 and 2 respectively) reflect an early-career trajectory, the practical, implementation-focused nature of his research—bridging theoretical SLAM methods with real-world ROS deployment and adaptive control—positions him as a promising contributor to industrial and service robotics. His work directly addresses the growing need for robots that can perceive, localize, and move intelligently in dynamic, human-populated spaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2