Muhammad Asif Khan

Papers

Total Citations

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About

Muhammad Asif Khan is a robotics researcher whose work centers on autonomous navigation, simultaneous localization and mapping (SLAM), and intelligent perception systems for mobile robots. His most cited paper, "Object Depth and Size Estimation Using Stereo-Vision and Integration With SLAM" (2024, 17 citations), addresses a critical challenge in autonomous robotics: enabling robots to accurately perceive object dimensions and depth without relying solely on expensive LiDAR sensors. By integrating stereo-vision depth estimation with SLAM, Khan’s work offers a cost-effective alternative that enhances navigation safety and efficiency in dynamic environments. His second highly cited contribution, "Haris: an Advanced Autonomous Mobile Robot for Smart Parking Assistance" (2024, 6 citations), demonstrates the practical application of these principles. The Haris system autonomously navigates crowded parking lots, using SLAM for real-time mapping and license plate recognition to track vehicle locations—eliminating the need for fixed infrastructure. Together, these papers highlight Khan’s focus on making autonomous systems more accessible, robust, and deployable in real-world settings. His research bridges computer vision, robotics, and SLAM, offering scalable solutions for smart cities and industrial automation.