Jeffrey Hudack
Papers
4
Total Citations
44
H-Index
4
About
Jeffrey Hudack is a researcher at the forefront of multi-robot coordination and autonomous navigation, with a particular focus on enabling robotic swarms to operate effectively under real-world constraints. His work addresses critical challenges in decentralized task allocation, especially in lossy communication networks where perfect information exchange cannot be assumed. Hudack’s most cited paper, “Chaotic Motion Planning for Mobile Robots” (2023, 18 citations), introduces a novel paradigm for generating unpredictable yet efficient trajectories—a vital capability for surveillance missions in adversarial environments. He further advances the field with “Decentralized Task Allocation in Lossy Networks” (2019, 13 citations), which bridges the gap between theoretical algorithms and practical deployment by modeling communication failures. His research on “Online Search of Unknown Terrains” (2022, 7 citations) and “Multi-Agent Sensor Data Collection with Attrition Risk” (2016, 6 citations) demonstrates a consistent focus on robust, risk-aware planning in hazardous or communication-denied settings. Hudack’s contributions are particularly impactful for defense, disaster response, and environmental monitoring applications, where robot teams must adapt to uncertainty and partial information. His work stands out for its pragmatic approach to foundational coordination problems, earning recognition among researchers developing resilient, real-world multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Decentralized Task Allocation in Lossy Networks: A Simulation Study13 citations · 2019
- 3
- 4Multi-Agent Sensor Data Collection with Attrition Risk6 citations · 2016