Papers
9
Total Citations
129
H-Index
6
About
Bradley Woosley’s research lies at the intersection of multi-robot coordination, real-time path planning, and modular self-reconfigurable robotics, with a strong emphasis on decision-making under communication and environmental uncertainties. His most impactful work, “Multi-robot information driven path planning under communication constraints” (28 citations), introduces a framework that balances exploration efficiency with the practical realities of limited connectivity—a critical challenge for field-deployed robot teams. Woosley has made foundational contributions to task allocation and motion planning in unknown environments, notably through his integrated approach in “Integrated real-time task and motion planning for multiple robots under path and communication uncertainties” (17 citations), which models path uncertainty as a Markov decision process to optimize task ordering. His work on modular self-reconfigurable robots, including real-time, distributed topology discovery using IR+XBee communication (23 citations), enables autonomous configuration sensing without prior knowledge—a key enabler for resilient, shape-shifting robot collectives. With over 120 total citations across his most-cited papers, Woosley’s research directly addresses the practical constraints of deploying multi-robot systems in disaster response and surveillance, where communication disruptions and dynamic obstacles are the norm. His transfer learning approach to path planning (22 citations) further demonstrates his commitment to scalable, adaptive autonomy.
Research Focus
Key Achievements
Top Papers
- 1Multi-robot information driven path planning under communication constraints28 citations · 2019
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- 5Multirobot task allocation with real-time path planning15 citations · 2013
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- 9Bid Prediction for Multi-Robot Exploration with Disrupted Communications5 citations · 2021