Muhammad Ahsan Fatwaddin Shodiq

National Yang Ming Chiao Tung University

Papers

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About

Muhammad Ahsan Fatwaddin Shodiq is a rising researcher in robotics and artificial intelligence, with a focus on autonomous navigation and robotic manipulation. His work centers on developing intelligent algorithms for robot path planning and grasping detection, addressing critical challenges in real-world automation. Shodiq’s most influential paper, “Robot path planning based on three-dimensional artificial potential field” (2025), has already garnered 18 citations, showcasing its impact on efficient 3D navigation in cluttered environments. In his 2024 study, “Enhancing Robotic Grasping Detection Accuracy With the R2CNN Algorithm and Force-Closure,” he introduced an improved rotational region convolutional neural network (R2CNN) that accurately predicts grasping bounding boxes for robotic arms—specifically designed for reaching supermarket goods—without requiring additional architectural modifications. This work bridges computer vision and force-closure analysis, advancing practical deployment in retail automation. With a growing citation record and innovative contributions to both path planning and grasping detection, Shodiq is establishing himself as a promising figure in intelligent robotics, offering scalable solutions for autonomous systems in dynamic, real-world settings.