Steven Farra

The University of Texas at San Antonio

Papers

1

Total Citations

6

H-Index

1

About

Steven Farra is a leading researcher in the field of dynamic legged locomotion and nonlinear control systems. His work focuses on developing robust control policies that enable legged robots to maintain balance and stability over large regions of their operational state space. Farra’s major contribution is a novel sampling-based approach to estimating the region of attraction (ROA) for highly nonlinear robotic systems, moving beyond traditional, often conservative, sum-of-squares optimization methods. This work, published in 2020, has already garnered 6 citations, signaling its growing influence in the robotics community. By allowing control policies to be validated across broader and more realistic conditions, Farra’s research directly advances the practical deployment of dynamically balancing robots in unstructured environments. His approach is particularly valuable for engineers seeking to push the limits of bipedal and quadrupedal locomotion, making his work a key reference for those aiming to bridge the gap between theoretical control guarantees and real-world robotic performance.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Control Policies for a Large Region of Attraction for Dynamically Balancing Legged Robots: A Sampling-Based Approach
6 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: The University of Texas at San Antonio

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago