Namya Bagree

Carnegie Mellon University

Papers

2

Total Citations

11

H-Index

2

About

Namya Bagree is a robotics researcher whose work bridges perception, control, and multi-robot coordination. Her primary research areas include 3D perception for mobile robots, autonomous navigation in human-centric environments, and distributed control for high-speed multi-robot systems. Bagree’s most impactful contribution is her work on "Fast Staircase Detection and Estimation using 3D Point Clouds with Multi-detection Merging for Heterogeneous Robots" (2023, 8 citations), which addresses a critical challenge in enabling robots to navigate multi-level buildings autonomously. This work provides a robust, real-time method for detecting and estimating staircases, a key capability for robots operating in complex indoor environments designed for humans. Her second highly cited paper, "Distributed Optimal Control Framework for High-Speed Convoys: Theory and Hardware Results" (2023, 3 citations), tackles the counterintuitive problem of maintaining tight formations at high speeds, offering both theoretical foundations and experimental validation. This work has practical implications for coordinated fleets in logistics, search-and-rescue, and autonomous transportation. Bagree’s research is notable for its emphasis on real-world deployment, combining algorithmic innovation with hardware implementation. Her work is particularly relevant for students and researchers interested in field robotics, autonomous navigation, and multi-agent systems, demonstrating how theoretical advances can translate into practical robotic capabilities.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Fast Staircase Detection and Estimation using 3D Point Clouds with Multi-detection Merging for Heterogeneous Robots
8 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Carnegie Mellon University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago