Peter C. Niedfeldt
Papers
1
Total Citations
8
H-Index
1
About
Peter C. Niedfeldt’s research centers on multi-robot systems, with a particular focus on distributed simultaneous localization and mapping (SLAM) and sensor fusion for large-scale, GPS-denied environments. His most cited work, "Distributed map fusion with sporadic updates for large domains" (2015, 8 citations), addresses a critical bottleneck in robotic exploration: how teams of robots can efficiently build and merge individual maps without continuous, high-bandwidth communication. Niedfeldt’s approach enables robots to operate in parallel, reducing exploration time while mitigating the effects of drifting sensor biases—a key challenge for autonomous systems operating in unknown terrain. This contribution is foundational for scalable, resilient multi-agent mapping, with implications for search-and-rescue, planetary exploration, and autonomous warehouse logistics. While his citation count reflects a focused, emerging body of work, Niedfeldt’s research stands out for its practical emphasis on sporadic updates and large-domain applicability, bridging the gap between theoretical SLAM algorithms and real-world deployment constraints. His work is particularly valuable for students and researchers interested in distributed robotics, sensor fusion, and the engineering of robust, communication-limited autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Distributed map fusion with sporadic updates for large domains8 citations · 2015