Victor Vu

The University of Texas at Austin

Papers

3

Total Citations

92

H-Index

3

About

Victor Vu is a leading researcher in robotics and artificial intelligence, with a primary focus on humanoid locomotion and multi-agent systems. His most significant contributions lie in the design and optimization of omnidirectional walking algorithms for humanoid robots, a critical challenge in dynamic, real-world environments. Vu’s work on the UT Austin Villa team, which won the RoboCup 2011 3D Simulation Competition, is particularly notable. His key paper on the subject, with 51 citations, details a winning approach that combined a robust walk engine with a learning architecture for parameter optimization, originally validated on a physical Nao robot. This work, alongside his team’s championship report (31 citations), established a benchmark for simulated soccer agents. By integrating locomotion, perception, and decision-making, Vu’s research has advanced the state of the art in autonomous robotics, demonstrating how simulated environments can accelerate the development of algorithms deployable on real hardware. His achievements highlight the power of simulation-driven innovation in competitive, multi-robot domains.

Research Focus

Key Achievements

3
H-Index
3
Papers
92
Total Citations
31
Avg Citations/Paper
🏆 Most Cited Paper
Design and Optimization of an Omnidirectional Humanoid Walk: A Winning Approach at the RoboCup 2011 3D Simulation Competition
51 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: The University of Texas at Austin

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago