Dang Quy Phan

About

Dang Quy Phan is a rising researcher in the field of robotics, with a focused interest in human-robot collaboration and intelligent manipulation. His work centers on developing advanced control systems that enable robots to work seamlessly alongside humans, particularly through context-aware interactions and the fusion of complex motion primitives. Phan’s most cited paper (8 citations) introduces a multi-controller architecture that integrates uni-axial motion with a real-time operating system, allowing for more adaptive and responsive human-robot collaboration. His more recent work (2025, 5 citations) tackles the challenge of smart manipulation by proposing a hierarchical framework that fuses pushing and grasping actions. This approach aims to achieve higher success rates when handling unknown objects, a critical step toward more versatile and autonomous robotic systems. By addressing the intricate fusion of motion primitives, Phan is contributing to the next generation of robotic control, where adaptability and precision are paramount. His research holds promise for applications in manufacturing, assistive robotics, and any domain requiring dexterous, collaborative manipulation.

Research Focus

Key Achievements

Top Papers

1. 1
   Implementation of multiple controllers for context-inspired collaboration between human and robot by integrating the uni-axial motion and real-time operating system

   8 citations · 2023
2. 2
   Approaching Collaborative Manipulation by Pushing-Grasping Fusion

   5 citations · 2025

Key Collaborators

Contact & Links