Collaborative Research: NeTS: Small: Joint Sensing and Communication with Millimeter-Wave Backscatter Tags for Multi-Agent Systems.

About This Grant

The convergence of sensing and communication technologies is becoming increasingly critical in emerging multi-agent systems, such as robot swarms, autonomous vehicles and virtual reality. These systems require both precise spatial awareness for coordination and real-time data exchange for collaborative decision making. However, existing solutions face fundamental limitations. Optical tracking systems are expensive and sensitive to occlusion, while Radio Frequency-based systems struggle to achieve comparable accuracy. Moreover, existing wireless solutions cannot simultaneously deliver the high-precision spatial tracking and high-throughput data exchange needed for real-time coordination in dynamic environments. A unified solution that enables both high-precision tracking and efficient communication remains an open challenge. This project tackles the above problem. Developing such new wireless technology is strategically important for setting the US as the leader in 6G and its applications. The proposed research is interdisciplinary in nature and will have a significant impact on different aspects of the society such as education, smart environment, health, robotics, warehouse automation and emergency response. The goal of this project is to enable precise spatial awareness and real-time sensor data communication using millimeter-wave (mmWave) backscatter technology. To achieve this, it first designs and fabricates novel backscatter tags that overcomes environmental interference and achieves submillimeter position accuracy and sub-degree orientation tracking. Then, to enable communication, it incorporates ultra-low power designs that directly encode analog sensor data into backscatter signals and develops an add-on receiver module for radars that enables data streaming for digital sensors. Finally, the system will be integrated into multi-robot systems performing collaborative perception tasks like 3D object detection and mapping. By combining hardware innovations, advanced algorithms, and system integration, this project provides a robust and energy efficient platform that enables new possibilities in networked multi-agent applications where both precise spatial coordination and real-time data sharing are essential. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.