Papers
8
Total Citations
64
H-Index
5
About
Bryce Doerr’s research lies at the intersection of robotics, autonomy, and distributed intelligence, with a focus on enabling large-scale robotic systems to sense, map, and act in uncertain environments. His key contributions span gas distribution mapping and path planning for very large-scale robotic (VLSR) systems, where he pioneered decentralized Hilbert maps to create scalable, probabilistic representations of environments—work that has garnered over 21 citations. Doerr is also a leading voice in swarm control, applying random finite set theory to manage the complexity and uncertainty of hundreds or thousands of agents, achieving efficient centralized and decentralized coordination. His most notable achievement is the ReSWARM microgravity flight experiments, which demonstrated real-world planning, control, and model estimation for on-orbit close proximity operations, including autonomous assembly—a critical step toward future space infrastructure. With additional work on motion planning using LQR-RRT* and nonlinear MPC for on-orbit assembly, Doerr’s research has practical impact in both terrestrial and space domains. His citation record, while still growing, reflects a young researcher whose ideas are shaping the future of autonomous, scalable robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2Control of Large Swarms via Random Finite Set Theory11 citations · 2018
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