Alireza Zamanian

Papers

Total Citations

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About

Alireza Zamanian’s research centers on autonomous robotics, with a particular focus on obstacle detection, motion estimation, and dynamic path planning for mobile systems. His most-cited work, “Estimation of Moving Obstacle Dynamics with Mobile RGB-D Camera” (2017, 3 citations), addresses a critical challenge in autonomous navigation: accurately predicting the velocity and acceleration of moving obstacles using only on-board RGB-D sensors. By enabling robots to anticipate obstacle trajectories rather than simply react to static positions, Zamanian’s approach enhances path optimization and safety in real-time environments. This contribution is especially relevant for applications in service robotics, autonomous vehicles, and drone navigation, where dynamic surroundings demand rapid, informed decision-making. Though his citation count is modest, the work reflects a thoughtful integration of computer vision and control theory, laying groundwork for more adaptive robotic systems. Zamanian’s research appeals to students and engineers interested in bridging perception and motion planning, offering practical methods for robots to navigate cluttered, unpredictable spaces with greater autonomy and reliability.