Dinh Hong Toan

Papers

Total Citations

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About

Dr. Dinh Hong Toan is a researcher at the forefront of socially aware robotics, with a primary focus on integrating deep learning into autonomous navigation systems. His most cited work, "Deep Learning-based Multiple Objects Detection and Tracking System for Socially Aware Mobile Robot Navigation Framework" (2018, 9 citations), addresses a critical bottleneck in human-robot interaction: enabling robots to perceive and track multiple dynamic objects, including people, in real time. This contribution provides the essential perceptual foundation for higher-level social navigation modules, allowing robots to move safely and naturally among humans. By leveraging deep learning for robust detection and tracking, Dr. Toan’s research helps bridge the gap between raw sensor data and intelligent, context-aware robot behavior. His work is particularly valuable for developing mobile robots that can operate in crowded, unstructured environments, such as hospitals, shopping malls, or public spaces. With a growing citation footprint, Dr. Toan’s research continues to influence the design of socially compliant robotic systems, making him a notable contributor to the fields of computer vision, deep learning, and autonomous navigation.