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About

Duong Dinh Tu is a robotics researcher focused on advancing autonomous navigation, control systems, and fault tolerance for mobile and industrial robots. His work bridges practical implementation and theoretical innovation, with key contributions in low-cost mapping systems, adaptive control, and actuator fault management. His most cited paper, "The Practice of Mapping-based Navigation System for Indoor Robot with RPLIDAR and Raspberry Pi" (2021, 10 citations), demonstrates a cost-effective prototype integrating SLAM with Raspberry Pi and RPLIDAR A1, making indoor robot navigation more accessible. In "Adaptive Terminal Sliding Mode Control Using RBF Neural Network for Industrial Robot Manipulators" (2025, 5 citations), he introduces a robust control method that enhances precision and adaptability in complex industrial tasks. His work on fault tolerance, "Proposal of a Fault-tolerant controller for wheeled mobile robots with faulty actuators" (2023, 4 citations), presents an observer-based scheme to maintain performance despite actuator failures, critical for operational reliability. Tu’s research has significant impact on developing resilient, affordable robotic systems, with applications ranging from factory automation to service robotics. His contributions are shaping next-generation autonomous robots that are both intelligent and robust.