Stephen F. Rounds

John Deere (Germany), John Deere (United States)

Papers

3

Total Citations

140

H-Index

3

About

Stephen F. Rounds is a researcher whose work sits at the intersection of robotics, mobile systems, and distributed estimation theory, with a particular focus on cooperative localization for multi-agent systems. His most significant contribution lies in developing decentralized algorithms that enable teams of mobile robots, unmanned vehicles, and human agents to accurately determine their positions relative to one another without relying on centralized computation — a critical challenge in real-world deployments for surveillance, search and rescue, and autonomous delivery. Rounds' most influential work, "Cooperative Localization for Mobile Agents: A Recursive Decentralized Algorithm Based on Kalman-Filter Decoupling" (2016), has garnered 93 citations and introduced an elegant approach to decoupling the Extended Kalman Filter framework across distributed agents. His earlier foundational paper (2014, 36 citations) established the theoretical bridge between centralized and decentralized implementations, while subsequent work addressed practical network challenges such as message dropouts (2015, 11 citations), demonstrating robustness under real communication constraints. Collectively, his research advances the feasibility of deploying large-scale autonomous agent networks in resource-limited environments, making meaningful contributions to both theoretical estimation frameworks and applied robotics systems.

Research Focus

Key Achievements

3
H-Index
3
Papers
140
Total Citations
47
Avg Citations/Paper
🏆 Most Cited Paper
Cooperative Localization for Mobile Agents: A Recursive Decentralized Algorithm Based on Kalman-Filter Decoupling
93 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: John Deere (Germany), John Deere (United States)

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago