Max Robotics — Global Service Robot Directory + US Certification

About

Munir Zaman’s research lies at the intersection of mobile robotics, sensor fusion, and precise localization, with a particular focus on visual odometry and time synchronization. His work addresses fundamental challenges in robot navigation—especially in low-texture and constrained environments like underground culverts—where wheel slippage and sensor timing errors degrade performance. Zaman’s major contributions include developing novel methods for high-precision relative localization using monocular and stereo cameras, achieving pose estimates comparable to wheel odometry but resistant to kinematic errors. He also proposed innovative algorithms for interval-based time synchronization and time delay estimation in sensor data, enabling more accurate fusion of vision and odometry for mobile robots. His most-cited paper (2005, 10 citations) introduced a novel approach to synchronizing odometry and vision data without restricting robot motion, directly improving localization. Another key work (2014, 9 citations) applied visual odometry to pipe inspection robots, addressing real-world maintenance challenges in Malaysian infrastructure. Across his publications, Zaman has accumulated over 50 citations, demonstrating steady impact in the robotics community. His work on systematic odometry error models for synchronous drive robots further underscores his commitment to rigorous, practical solutions for autonomous navigation.