Regina Rex

Texas A&M University

Papers

1

Total Citations

2

H-Index

1

About

Regina Rex is a roboticist specializing in motion planning and autonomous navigation, with a particular focus on leveraging environmental topology to improve algorithmic efficiency. Her work bridges the gap between traditional path planning and real-world constraints, introducing novel methods that incorporate annotated skeletons—topological abstractions enriched with spatial properties like obstacle clearance, terrain conditions, and resource accessibility. In her most cited paper, "Annotated-skeleton Biased Motion Planning for Faster Relevant Region Discovery" (2020), Rex demonstrates how integrating these annotations into the planning process accelerates the discovery of task-relevant regions, enabling robots to make smarter, context-aware decisions. While her citation count is still growing—reflecting the early stage of her career—her contributions are notable for their practical potential in field robotics, search-and-rescue, and planetary exploration. Rex’s work stands out for its elegant fusion of geometric reasoning and environmental semantics, offering a promising direction for more adaptive and efficient autonomous systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Annotated-skeleton Biased Motion Planning for Faster Relevant Region Discovery
2 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Texas A&M University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago