As the autonomy of robots performing manipulation or legged locomotion tasks increases, they require an ever-growing amount of computational resources to successfully perceive their environment and make decisions. Yet, mobile robots are fundamentally constrained by weight, shape and power autonomy which impose important limits on the computational capabilities they can carry. As a possible answer to such dilemma, cloud robotics aims to move computation to remote servers, but it has thus far remained an elusive approach for tasks that necessitate low delay communication and high data bandwidth between the robot and the cloud. Such tasks include control, planning and perception algorithms for object manipulation and legged locomotion. The 5th generation of cellular network technology (5G) could revolutionize cloud robotics as it promises unprecedented access to high bandwidth and low latency wireless communication. Yet, formidable challenges remain to ensure communication reliability, safety of robotic operation under communication degradation, and scalability to multi-robot systems. This project aims to fully incorporate 5G technology into robotics systems performing complex manipulation and locomotion tasks. It will develop novel perception, control and planning algorithms that optimally distribute computations between robots and the cloud for guaranteed safe robotic operation. Ultimately, these algorithms will accelerate the ubiquitous deployment of untethered 5G-enabled robots in human environments and unlock a large range of applications for healthcare, service and industrial robotics.

The project takes a holistic approach to control, perception and communication to establish the foundations of edge-based wireless real-time action-perception loops for autonomous robots. It is organized along four main thrusts of research. First, it will investigate novel optimal control and planning algorithms distributed between the network edge and the robot with performance guarantees under communication degradation. Second, it will propose efficient computational partitioning techniques for real-time perception using multi-modal sensing with high data rates. Third, it will characterize 5G specific communication channels in a robotics environment via experiments and simulations and design new mmWave communication protocols tailored for real-time robotic action-perception loops. Finally, extensive experiments on single and multi-robot systems, including fixed and mobile manipulators and a quadruped robot, will demonstrate the unique capabilities of 5G-enabled robotic systems. The outreach activities of the project will contribute to lowering barriers to entry for scientists and industries that seek to exploit 5G-enabled robotics through open-source distribution of algorithms and dissemination of results via NYU WIRELESS. This effort will contribute to the education of undergraduate and graduate students, leveraging its outcomes for curriculum development and offering supervised projects with the possibility to work directly on state-of-the-art experimental platforms.

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.

Project Start
Project End
Budget Start
2019-10-01
Budget End
2022-09-30
Support Year
Fiscal Year
2019
Total Cost
$749,999
Indirect Cost
Name
New York University
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10012