CNS: An Edge-Based Approach to Robust Multi-Robot Systems in Dynamic Environments
CNS: An Edge-Based Approach to Robust Multi-Robot Systems in Dynamic Environments
NSF Award #2245156 · CNS / CISE-MSI · 2022–2026
Project Summary
Multi-robot systems consist of autonomous robots interacting in a shared environment to achieve common goals. They are widely used in real-world application domains such as transportation, disaster management, as well as warehousing and manufacturing. This project develops an efficient, robust, and secure multi-robot system, called EdgeRobot. EdgeRobot establishes an edge computing based architecture and algorithmic framework to facilitate multi-robot collaboration and coordination in dynamic environments, providing new models, architectures, and theory for coordinated multi-robot systems.
In addition, this project builds research capacity for training underrepresented students through a partnership of six geographically diverse minority-serving institutions (MSIs) across the United States. The cross-institutional collaboration boosts research capacity at all participating institutions and provides integrative research and education experience to underrepresented minority students.
Technical Approach
The project consists of three research thrusts:
- Edge computing infrastructure: Optimal and location-aware computing services for collaborative robots; reinforcement learning-based algorithms for multi-robot scheduling and routing, modeled as variants of the prize-collecting traveling salesman problem.
- Multi-agent reinforcement learning: Enables teams of robots to operate, learn, and adapt in dynamic and human-populated environments robustly and safely — supporting tasks such as cooperative target tracking.
- Security for edge collaboration: Integrating modern cryptographic and security primitives to secure the collaboration among edge nodes in multi-robot systems; building a shared autonomy model at the EdgeRobot–human interface.
Research Team
| Role | Investigator | Institution |
|---|---|---|
| PI (Mason) | Dr. Md Tanvir Arafin | George Mason University |
| Lead PI | Dr. Kewei Sha | University of North Texas |
| Co-PI | Dr. Bin Tang | Cal State Dominguez Hills |
| Co-PI | Dr. Lily Ma | CUNY |
| Co-PI | Dr. Pooyan Fazli | Arizona State University |
Partner MSIs: University of Houston–Clear Lake · University of Michigan Flint · CUNY-New York City College of Technology · Morgan State University · San Francisco State University · California State University Dominguez Hills
Funding
NSF Award #2245156 Collaborative Research: CISE-MSI: DP: CNS: An Edge-Based Approach to Robust Multi-Robot Systems in Dynamic Environments Total Project Award: $600,000 · Mason Share: $95,000 · Period: Oct. 2022 – Aug. 2026 Funded in part under the American Rescue Plan Act of 2021 (Public Law 117-2).