M. K. Zakaria

Papers

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About

M. K. Zakaria’s research focuses on advancing autonomous robotics through innovative, low-cost computer vision techniques. His work addresses fundamental challenges in robot navigation and manipulation, particularly in depth perception and obstacle avoidance using monocular vision systems. In his most cited work, “Robot path obstacle locator using webcam and laser emitter” (2010, 8 citations), Zakaria introduced a practical method for distance measurement by combining a standard webcam with a laser pointer. This approach enables robots to calculate distances to obstacles and navigate toward targets while avoiding collisions, offering a cost-effective alternative to expensive sensor systems. Expanding on this foundation, his paper “Depth estimation from monocular vision using image edge complexity” (2011, 3 citations) explores how changes in image edge complexity during camera motion can be used to estimate depth for robotic arm control. This work contributes to safer, more precise autonomous manipulation by preventing collisions with target objects. Zakaria’s contributions are particularly valuable for researchers and students working on accessible robotics solutions, demonstrating how simple hardware and clever algorithms can solve complex perception problems in real-world environments.