Papers
14
Total Citations
397
H-Index
10
About
Samuel Barrett is a leading researcher in multi-robot systems and artificial intelligence, with a particular focus on enabling autonomous agents to collaborate effectively with unfamiliar teammates—a challenge known as ad hoc teamwork. His pioneering work, including the highly cited "Cooperating with Unknown Teammates in Complex Domains" (72 citations) and "Making Friends on the Fly" (67 citations), has laid the foundation for robots to dynamically form teams without pre-coordination, a critical capability for real-world deployments. Barrett also made significant contributions to humanoid locomotion, developing an award-winning omnidirectional walk for the Nao robot that powered the UT Austin Villa team to victory at RoboCup 2011 and 2012. His research bridges simulation and reality, as demonstrated in "Humanoid Robots Learning to Walk Faster" (65 citations), where he optimized walking parameters across domains. With over 370 total citations, Barrett's work has been recognized through multiple RoboCup championships and continues to influence the fields of cooperative robotics, machine learning, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1
- 2Making friends on the fly: Cooperating with new teammates67 citations · 2016
- 3
- 4
- 5
- 6A bio-inspired apposition compound eye machine vision sensor system29 citations · 2009
- 7The RoboCup 2013 drop-in player challenges: Experiments in ad hoc teamwork21 citations · 2014
- 8Making Friends on the Fly: Advances in Ad Hoc Teamwork14 citations · 2015
- 9Leading the Way: An Efficient Multi-robot Guidance System11 citations · 2015
- 10UT Austin Villa 2012: Standard Platform League World Champions11 citations · 2013