Papers

12

Total Citations

192

H-Index

6

About

David Baran is a robotics and autonomous systems researcher whose work spans multi-robot coordination, mobile robot navigation, and military communications networks. His most influential contribution, "Application of Multi-Robot Systems to Disaster-Relief Scenarios with Limited Communication" (2016, 80 citations), established foundational approaches for deploying robot teams in degraded communication environments—a critical challenge in real-world emergency response. Complementing this, his research on stairway modeling from dense depth imagery (2013, 43 citations) advanced autonomous multi-floor exploration by bridging the gap between stairway detection and path planning, enabling robots to navigate complex indoor environments more intelligently. Baran's earlier career centered on military robotics and tactical communications, with notable contributions to ad hoc networking for unmanned ground vehicles and soldier-robot wireless networks, reflecting sustained collaboration with the U.S. Army Research Laboratory. His work on human-robot teaming and scalable robotic controllers further demonstrates a commitment to making autonomous systems practically usable by soldiers in the field. Across his career, Baran has consistently addressed the intersection of autonomy, communication constraints, and human-machine collaboration—making his research particularly relevant for students interested in field robotics, disaster response systems, and defense applications of autonomous technology.

Research Focus

Key Achievements

6
H-Index
12
Papers
192
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Application of Multi-Robot Systems to Disaster-Relief Scenarios with Limited Communication
80 citations · 2016
📈 Most Prolific Year: 2016 (2 Papers)
🤝 Key Collaborators: 30
🏛 Institutions: DEVCOM Army Research Laboratory, K Lab (United States)

Top Papers

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    A Soldier-Robot Ad Hoc Network
    23 citations · 2007
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago