Muhammad Saad Aslam

National University of Sciences and Technology

Papers

Total Citations

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About

Muhammad Saad Aslam is a robotics researcher whose work centers on autonomous navigation, sensor fusion, and simultaneous localization and mapping (SLAM) for mobile robots. His most-cited paper, "An RPLiDAR based SLAM equipped with IMU for Autonomous Navigation of Wheeled Mobile Robot" (2020), tackles the critical challenge of enabling robots to navigate accurately in environments without external mapping aids. By integrating LiDAR with an Inertial Measurement Unit (IMU), Aslam’s approach enhances the robustness and precision of SLAM systems—a foundational technology for autonomous vehicles and service robots. This work has garnered 8 citations, reflecting its relevance to researchers developing low-cost, reliable navigation solutions. Aslam’s contributions are particularly notable for addressing real-world constraints, such as sensor noise and environmental unpredictability, making his research valuable for practical deployment in wheeled mobile robots. His focus on accessible hardware (e.g., RPLiDAR) and algorithmic efficiency positions him as a key voice in advancing autonomous systems for industrial and domestic applications. For students and researchers, Aslam’s work offers a clear entry point into understanding how sensor integration can overcome the limitations of individual navigation technologies.