Dinh Tung Vo
Papers
5
Total Citations
62
H-Index
5
About
Dinh Tung Vo is a robotics researcher whose work sits at the critical intersection of autonomous navigation, reconfigurable systems, and human safety. His primary research areas include path planning for emergency evacuation, deep reinforcement learning for complete coverage, and the design of transformable service robots. Vo’s most impactful contribution is his 2023 paper on robot-aided human evacuation optimal path planning for fire drills, which has garnered 29 citations, highlighting its relevance to real-world safety applications. He has also pioneered the use of deep reinforcement learning to achieve complete coverage planning with trapezoid-based and polyiamonds-based reconfigurable robots, earning 14 and 9 citations respectively. His work on staircase navigation and maintenance using self-reconfigurable service robots (5 citations) demonstrates a commitment to practical, multi-terrain mobility. Additionally, Vo has contributed to fundamental robotics with a study on the kinematic and dynamic accuracy of spherical mechanisms (5 citations), which has implications for precision orienting devices in medical and camera systems. Through his innovative integration of learning-based control and adaptive hardware, Vo is shaping the future of autonomous service robots capable of operating in complex, human-centric environments.
Research Focus
Key Achievements
Top Papers
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- 5Kinematic and dynamic accuracy of spherical mechanisms5 citations · 2022