Razif Rashid

Universiti Teknologi Petronas, Petronas (Malaysia)

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About

Razif Rashid is a researcher whose work lies at the intersection of mobile robotics, intelligent control, and bio-inspired optimization. His primary contributions focus on solving the critical challenge of autonomous robot navigation in complex environments. Rashid’s most influential work, "Mobile robot path planning using Ant Colony Optimization" (2016), with 48 citations, demonstrates a novel application of swarm intelligence to compute optimal, collision-free paths for mobile robots, outperforming traditional methods on maps of varying complexity. This paper established a benchmark for nature-inspired path planning. Earlier foundational contributions include "Differential Drive Wheeled Mobile Robot Control Using Fuzzy Logic Techniques" (2010, 25 citations) and "Fuzzy-based Navigation and Control of a Non-Holonomic Mobile Robot" (2010, 20 citations). In these works, Rashid pioneered the use of fuzzy logic to imbue robots with human-like reasoning for simultaneous target tracking and reactive obstacle avoidance, effectively bridging the gap between theoretical control models and practical, real-world deployment. Collectively, his research provides a robust framework for intelligent, adaptive, and computationally efficient robot navigation, making him a notable figure in the field of autonomous systems.