Max Robotics — Global Service Robot Directory + US Certification

About

Seng Fat Wong is a robotics researcher whose work focuses on teleoperation, haptic feedback, and mobile robot navigation—critical areas for advancing intelligent automation and human-robot interaction. His most cited paper, "Design and Development of a Teleoperated Telepresence Robot System With High-Fidelity Haptic Feedback Assistance" (2024, 17 citations), introduces a novel system that combines a master device with a collaborative slave robot to deliver precise haptic feedback for high-stakes tasks like explosive ordnance disposal (EOD). This work demonstrates his commitment to enhancing operator safety and task accuracy in dangerous environments. Wong also contributed to the field of autonomous navigation with his 2019 paper on an anti-disturbance vSLAM algorithm using RBF neural networks (10 citations), addressing the need for robust, marker-free guidance in industrial AGVs—a key enabler for Industry 4.0. Earlier, his 2018 study on two-wheeled robot control (4 citations) tackled the challenge of underactuated systems under nonlinear damping and road disturbances, showcasing his depth in practical dynamics and controller design. With a growing citation footprint, Wong’s research bridges theoretical control and real-world deployment, making him a notable figure in telepresence and mobile robotics.