About

Gray C. Thomas is a robotics researcher whose work spans humanoid robot control, legged locomotion, wearable exoskeletons, and compliant actuation systems. He is perhaps best known for his contributions to momentum-based control frameworks for floating-base robots, most notably his highly cited 2016 paper on the humanoid robot Atlas (255 citations), which introduced a quadratic programming approach to reconcile competing motion tasks — a foundational contribution to whole-body control in robotics. His early career also included prize-winning work on the DARPA Virtual Robotics Challenge as part of Team IHMC (86 citations), demonstrating real-world impact in disaster-response robotics. Thomas has made significant theoretical advances in series-elastic actuator control, biped locomotion stability, and operational space control for point-foot robots, reflecting a deep interest in bridging mathematical rigor with physical hardware. More recently, his research has expanded into assistive wearable technology, including a versatile knee exoskeleton designed to reduce quadriceps fatigue across occupational tasks (38 citations) and novel spring architectures for compliant robots. Across his career, Thomas's work consistently addresses the challenge of making robots simultaneously safe, dynamic, and adaptable — qualities essential for machines operating alongside humans.

Research Focus

Key Achievements

9
H-Index
21
Papers
564
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Design of a Momentum-Based Control Framework and Application to the Humanoid Robot Atlas
255 citations · 2016
📈 Most Prolific Year: 2016 (3 Papers)
🤝 Key Collaborators: 59
🏛 Institutions: The University of Texas at Austin, Beijing Jiaotong University, University of Michigan–Ann Arbor, Walker (United States), Texas A&M University, Franklin W. Olin College of Engineering

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago