Decentralized Computing on Autonomous Mobile Platforms
This project studies how unstable wireless connections affect decentralized algorithms used in autonomous robots and UAVs, focusing on optimization, allocation, and signal processing.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: May 1, 2025 (Application Deadline)
Funding Amounts: $99,200 stipend plus $3,000 travel allowance; typical tenure 2-3 years postdoctoral fellowship
Summary: Supports postdoctoral research on decentralized algorithms for autonomous mobile platforms under dynamic wireless network conditions, focusing on optimization, task allocation, and graph signal processing.
Key Information: Open to U.S. citizens and permanent residents; requires contacting a Research Adviser prior to applying; relocation and health insurance benefits included.
Description
This fellowship opportunity at the Naval Research Laboratory (NRL) focuses on studying the impact of dynamic and volatile wireless communication environments on the performance of decentralized algorithms critical to autonomous mobile platforms such as Unmanned Aerial Vehicles (UAVs) and other robotic systems. The research aims to analyze, develop, and empirically evaluate decentralized numerical optimization, task allocation, and graph signal processing algorithms under time-varying network topologies and unstable wireless links.
A key component of the project is the development of an integrated multi-agent system emulator with realistic communication capabilities to serve as a virtual testbed for reproducible experiments. The research involves theoretical algorithm analysis, implementation, mobile network experimentation, data analysis, model extraction, validation, and dissemination of findings.
This program is designed for postdoctoral researchers interested in advancing distributed autonomy, collaborative multi-agent systems, and decentralized learning in mobile robotic platforms.
